omrajkumar / Market-Basket-Analysis-on-Food-Items

Frequent Itemsets via Apriori Algorithm Apriori function to extract frequent itemsets for association rule mining We have a dataset of a mall with 7500 transactions of different customers buying different items from the store. We have to find correlations between the different items in the store. so that we can know if a customer is buying apple, banana and mango. what is the next item, The customer would be interested in buying from the store.

Amazon Fine Foods Analysis

Context

This 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.

Contents Reviews.csv: Pulled from the corresponding SQLite table named Reviews in database.sqlite database.sqlite: Contains the table 'Reviews'

Data includes:

Reviews from Oct 1999 - Oct 2012 568,454 reviews 256,059 users 74,258 products 260 users with > 50 reviews wordcloud

Acknowledgements See this SQLite query for a quick sample of the dataset.

If you publish articles based on this dataset, please cite the following paper:

J. McAuley and J. Leskovec. From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews. WWW, 2013.