期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：7
页码：13782
DOI：10.15680/IJIRSET.2017.0607148
出版社：S&S Publications
摘要：Recommendation systems are widely used by e-commerce websites to recommend items to users.Recommender systems apply knowledge discovery techniques to the problem of making personalizedrecommendations for information, products or services during a live interaction. Item based techniques first analyse theuser-item matrix to identify relationships between different items, and then use these relationships to indirectlycompute recommendations for users. In this paper a new algorithm for item based recommendation system usingcollaborative filtering is proposed. The algorithm is used to recommend items to a user. The algorithm considersprevious patterns of other users which are having same taste. The system predicts ratings for given items for givenusers. The algorithm is implemented for a standard data set and results conclude that the proposed algorithm performsbetter than the other existing algorithms.
关键词：Recommendation Systems; Web Usage Mining; Collaborative Filtering
