Recommender System Survey: Clustering to Nature Inspired Algorithm
For e commerce, besides increasing cross selling by suggesting additional products for the customer to purchase, Recommender Systems (RS) are an effective way to increase customer satisfaction and consequently, customer loyalty. Thus personalization tools like RS is essential to support users to identify interesting products and services by considering the opinions of thousands if not millions of people all over the world. This article offers an outline of RS, their types as well as existing challenges. Further it also emphasizes on various evaluation metrices to be used for recommender system performance analysis. This paper surveys various existing algorithms that solve some problem of recommender system and the results of various nature inspired algorithms for recommender system are compared.