INSIDE RECOMMENDATION SYSTEM: SURVEY, RESEARCH AREA

With the increase in E - commerce, Recommendation Systems are getting popular to provide recommendations of various items (movies, books, music) to users. To build the Recom mendation System (RS) , Collaborative Filtering (CF) techniques are proven efficient. The main t wo C ollaborative Filtering techniques are User - Based and Item - B ased, but from survey it can be said that item - based CF provides better recommen dations. A novel approach , Ratio - B ased CF provide s recommendat ion depending upon the item has more accuracy amongst item - based CF technique. The problem with CF techniques is more execution time i.e. O(mn). To improve the execution time a parallel platform or techni que can be adopted to reduce the time complexity of recommendation system. Hence, for better and faster reco mmendation parallel Ratio - Based Collaborative F iltering algorithm should be used.