A review on recommender systems

Recommender systems have turn into an important recommendation technique on the web and are widely used for recommendation of different items. On web huge amount of data is available online, the need of analysis and personalization systems is increasing permanently. This paper presents introduction to the categories of recommender systems and different recommendation techniques are mainly classified into three categories: collaborative filtering, content based filtering and hybrid filtering. This paper also discusses challenges of recommender system. Every method has its weakness and strengths that relate to the domain.