A Hybrid searching strategies for recommendation systems

The internet and world wide web have brought us an abundant information in various fields and due to the information overloading , it is very hard to find out relevant content so, Recommendation System come into existence. The main aim of Recommendation system is to provide suggestions to a user. The suggestions relevant to decision-making processes, like what items to buy, which music to listen to, which online news to read, or which movie is best one. The benefit of recommendation system depends on utility of the system. The utility can be measured in terms of accuracy, flexibility, reliability, sparsity. The proposed work mainly applies an association mining over clustering to recommend the best suitable items to the user by generating better rules. The Clustering is applied to the group of user’s set into k clusters by applying k-means algorithm and Association mining is used for generating the rules.