Recommender System using Hybrid Approach

Efforts from multiple disciplines involving various fields like Human Computer Interaction, Marketing, or Consumer Behavior, Data Mining, Adaptive User Interfaces, Artificial intelligence, Statistics, Information Technology and Decision Support Systems contribute to development of recommender system. In today's scenario, there exists different recommender algorithms used for filtering data and providing user with best suitable choices. The way people find products and information is greatly affected by recommender systems. Recommender system is thus, a tool to reduce the overloaded data. In this paper, we propose a new algorithm Composite Search that combines few filtering algorithms and presents refined result, eliminating drawbacks of other algorithms. We present our approach that processes data and provides more filtered result.