Amazon Fine Food Review
Amazon Fine Food Review dataset consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.
Number of reviews : 568,454
Number of users : 256,059
Number of products : 74,258
Timespan : Oct 1999 - Oct 2012
Number of Attributes/Columns in data : 10
Attribute Information :
Id - serial number
ProductId - unique identifier for the product
UserId - unqiue identifier for the user
ProfileName - name which is used by the user
HelpfulnessNumerator - number of users who found the review helpful
HelpfulnessDenominator - number of users who indicated whether they found the review helpful or not
Score - rating between 1 and 5
Time - timestamp for the review
Summary - brief summary of the review
Text - text of the review
Problem Statement : In this challenge, Given a review, we are determining whether the review is positive (Rating of 4 or 5) or negative (rating of 1 or 2).
P.S - A rating of 4 or 5 could be cosnidered a positive review. A review of 1 or 2 could be considered negative. A review of 3 is nuetral and ignored. This is an approximate and proxy way of determining the polarity (positivity/negativity) of a review.
Source : https://www.kaggle.com/snap/amazon-fine-food-reviews
Real-world/Business Objectives and Constraints :
- The cost of a mis-classification can be high.
- No strict latency concerns.
- It will help everyone to unterstand the insights of large scale online businesses.
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