Recommendation based on Clustering and Association Rules

Recommender systems play an important role in filtering and customizing the desired information. Recommender system are divided into 3 categories i.e collaborative filtering , content-based filtering, and hybrid filtering and they are the most adopted techniques being utilized in recommender systems. The paper mainly describe about the issues of recommendation system.The main aim of paper is to recommend the suitable items to the user, so for recommending the suitable items a better rule extraction is needed.Thus for better rule extraction Association mining is applied .The clustering method is also applied here to cluster the data based on similar characteristics .The propose methods try to eliminate certain problems such as sparsity, cold-start problem. So to overcome the certain problem association mining over clustering is used.