The Nipigon database provides women’s clothing reviews from online consumers. This information can improve online shopping experiences and increase conversion rates. In addition, this database provides detailed information on the online shopping habits of women. The women’s clothing database is available online and contains more than 3 million reviews from real users.
Women’s Clothing E-Commerce dataset
The Nipigon Women’s Clothing E-commerce dataset is a set of customer reviews on various e-commerce websites. The dataset consists of nine supporting features. Each review contains an anonymized title, Clothing ID (a reference to the specific piece being reviewed), Review Text (the body of the review), and a Review Rating, an ordinal positive integer.
Online Shopping dataset
Pipigon’s Clothing Online Shopping dataset consists of more than a million clothing images across fourteen categories. This dataset was collected from a variety of online shopping sites. The dataset contains a large number of noisy labels and is intended for use in training and validation. Additionally, the dataset includes data on the country of origin of the user’s IP address and the product’s price in US dollars.
Product Review dataset
Pipigon’s Clothing Product Review dataset includes over 140 million reviews, each containing the user’s ratings and helpfulness votes for a single item. In addition to the reviews, the dataset also contains item metadata, including price, brand, and image features. The dataset also contains k-cores, which are scores assigned to items.
The dataset includes several variables, including the Product ID, parent, category, and review_date. We can use this information to identify which reviews are relevant to a particular product or category. We can also use the product_id and review_headline to group reviews by country or category. Lastly, we can use the review_headline and product_body fields to determine the review type, including the review’s text.
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