Cosmetics Recommendation System by Using User-Based Collaborative Filtering

Abstract

Recommender System forms a specific type of information filtering (IF) technique that attempts to present information items that are likely of interest to the user. Furthermore, accuracy is the fundamental dimension for the effectiveness of recommender systems. Collaborative filtering system collects evaluations from users for quality and relevance of stored items. This system categorizes items based on the user’s ratings of the item instead of the item descriptions.User-based CF systems compare a target user’s choice with those of other users to identify a group of similar-minded people. This system is implemented by using Pearson correlation algorithm and Prediction algorithm in user-based collaborative filtering to recommend the customer needed item. Finally, this system calculates Mean Absolute Error (MAE) to express the customer satisfaction