Review Paper on Next Generation Collaborative Filtering of Data Based on Typicality Method

Collaborative clustering increases the researchers interest since from last decade for sfficient recommender systems. There are different methods presented for CF which is based on two different categories such as user based CF and item based CF. in user based CF, main task is to find out set of users who have similar favor patterns to a given user and recommend to the user those items that other users in the same set like. In item based CF method, main task is to provide a user with the recommendation on an item based on the item with high correlations. But exiting methods are having limitations likedata sparsity, recommendation accuracy and prediction error. Here, we have proposed novel efficient Expectation Maximization (EM) Clustering and typicality-based collaborative filtering recom-mendtion (EmTyCo). EmTyCo method is based on existing Tyco method by using efficient Expectation Maximization Algorithm for clustering purpose.