DEVELOPMENT OF INTEREST BASED COLLABORATIVE FILTERING RECOMMENDATION ENGINE

Recommender systems are used on the web for recommending products to users. Most of the electronic commerce sites have such systems. C ollaborative filtering is an important and popular technique for recommender system. In this paper, an expert system for movie recommendation is presented with new approach. This system is implemented using co clustering method. Category of the movie and r atings given by users are used to give recommendations. Users are interested in grouping items into categories and for each category; there can be corresponding user group who like items in that category. Finding interest of user in particular item group a nd grouping users of similar interest is distinguishable feature, which differentiate our approach from the previous works