Abstract:A product recommendation is basically a filtering system that seeks to predict and show the items that a user would like to purchase. It may not be entirely accurate, but if it shows you what you like then it is doing its job right. With the vast amount of data that the world has nowadays, Companies like Amazon use their huge amounts of data to give recommendations for users. Based on similarities among items, systems can give predictions for new items rating. Recommender systems use the user, item, and ratings information to predict how other users will like a particular item. The motivation for this project comes from the eagerness to get a deep understanding of recommender systems. In this project, a website has been developed that uses different techniques for recommendations namely Frequent Itemset and Association Mining using Apriori algorithm.
Keywords: Product Recommendation, Similar Data items, Machine Learning.
| DOI: 10.17148/IJARCCE.2021.10757