A survey on recommender systems

Motlatsi Liphoto, Chunling Du, Seleman Ngwira
<span title="">2016</span> <i title="IEEE"> 2016 International Conference on Advances in Computing and Communication Engineering (ICACCE) </i> &nbsp;
Recommender systems provide useful recommendations to a collection of users for items or products that might be of concern or interest to them. Its design depends on the data characteristics and the domain for which it will be applicable. The applications where recommender systems are used range from electronic products, books, movies, websites to even news articles and so on. The recommendations deal with predicting user's ratings that are yet to be consumed by users, based on the items
more &raquo; ... rated by them and recommend the top N items with the highest predicted ratings. Many algorithms try to improve the accuracy in predicting the top N items thereby improving the recommendation quality. This paper presents an overview of recommender systems and explores the various approaches to recommender systems.
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