oclar

Références:

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:oclar')
  • Descriptif :
The researchers of OCLAR Marwan et al. (2019), they gathered Arabic costumer reviews from Google reviewsa and Zomato website 
(https://www.zomato.com/lebanon) on wide scope of domain, including restaurants, hotels, hospitals, local shops, etc.
The corpus finally contains 3916 reviews in 5-rating scale. For this research purpose, the positive class considers
rating stars from 5 to 3 of 3465 reviews, and the negative class is represented from values of 1 and 2 of about 451 texts.
  • Licence : Aucune licence connue
  • Version : 1.1.0
  • Fractionnements :
Diviser Exemples
'train' 3916
  • Caractéristiques :
{
    "pagename": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "rating": {
        "dtype": "int8",
        "id": null,
        "_type": "Value"
    }
}