amazon_us_reviews

참조:

• 암호
• 허깅페이스

책_v1_01

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_01')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

시계_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Watches_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Personal_Care_Appliances_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Personal_Care_Appliances_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

모바일_전자제품_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Electronics_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Video_Games_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Games_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

디지털_소프트웨어_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Software_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Major_Appliances_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Major_Appliances_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Gift_Card_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Gift_Card_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

비디오_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Video_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

수하물_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Luggage_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

소프트웨어_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Software_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Video_Games_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Video_Games_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

가구_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Furniture_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

뮤지컬_악기_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Musical_Instruments_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

디지털_음악_구매_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Music_Purchase_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

책_v1_02

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_02')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

홈_엔터테인먼트_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Home_Entertainment_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

식료품_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Grocery_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

야외_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Outdoors_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

애완 동물_제품_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Pet_Products_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

비디오_DVD_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Video_DVD_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

의류_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Apparel_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

PC_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/PC_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

도구_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Tools_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

보석_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Jewelry_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

베이비_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Baby_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

홈_개선_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Home_Improvement_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

카메라_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Camera_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

잔디와 정원_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Lawn_and_Garden_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

사무실_제품_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Office_Products_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

전자 제품_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Electronics_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

자동차_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Automotive_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Video_Download_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Download_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

모바일_앱_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Apps_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

신발_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Shoes_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

장난감_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Toys_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

스포츠_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Sports_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

주방_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Kitchen_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

뷰티_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Beauty_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

음악_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Music_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Health_Personal_Care_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Health_Personal_Care_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

디지털_전자책_구매_v1_01

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_01')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

홈_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Home_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

무선_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Wireless_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

책_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

디지털_전자책_구매_v1_00

다음 명령을 사용하여 TFDS에서 이 데이터세트를 로드합니다.

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_00')

• 설명 :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• 라이선스 : 알려진 라이선스 없음
• 버전 : 0.1.0
• 분할 :

• 특징 :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}