Development of Context Based Collaborative Filtering System for Recommendation
Collaborative filtering, Context based collaborative filtering, Clustering, Recommender, User-Context
Recommender systems suggest items to users by utilizing the techniques of Collaborative filtering based on historical records of items that users have purchased. Recommender systems make use of data mining techniques to determine the similarity among a huge collection of data items, by analysing historical user data and then extracting hidden useful information or patterns. Goal of Collaborative filtering is finding the relationships among the individuals and the existing data items in order to further determine the similarity and provide recommendations. This paper, proposes the Context based Collaborative Filtering Recommender System, which can be used for any commercial online-marketing. Experimental evaluation of results and comparing them with traditional collaborative filtering approach, concludes that context based collaborative approach provide dramatically better performance than traditional-based algorithms, while at the same time providing better recommendation as per customer point of view.
Rohit M.Pawar, Mr.V.V.Bag. "Development of Context Based Collaborative Filtering System for Recommendation".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 3, pp.3137-3142, URL :https://rjwave.org/ijedr/papers/IJEDR1403038.pdf
Volume 2 Issue 3
Pages. 3137-3142
