Collaborative filtering-based recommender system: Approaches and research challenges

Abstract

Due to information explosion, huge number of items are present over web which makes it difficult for user to find appropriate item from available set of options. Recommender System (RS) overcomes the problem of information overload and suggests items that interest to a user. It has gained a lot of popularity in past decades and huge amount of work has been done in this field. Collaborative Filtering (CF) is the most popular and widely used approach for RS which tries to analyze the user's interest over the target item on the basis of views expressed by other like-minded users. This paper gives a brief idea of various approaches used for Recommender System and provides an insight of Collaborative Filtering technique. Here, we also discuss well-known methods for CF i.e. Memory-based, Model-based, and hybrid approaches and at last we focus on research challenges that need to be addressed.