Trends, problems and solutions of recommender system

Abstract

In this era of web, we have a huge amount of information overloaded over Internet. It becomes a herculean task for the user to get the relevant information. To some extent, the problem is being solved by the search engines, but they do not provide the personalization of data. So, to further filter the information, we need a recommendation engine. In this paper, we have described the various web recommender systems in use by some popular web sites on the internet like Amazon.com, LinkedIn.com, and YouTube.com etc. Further, we have described the various approaches used in the various recommender systems such as Content based, Collaborative and Hybrid recommender system. At the end of this paper, we focus on some of the main challenges faced by the web recommender systems and analyze some techniques to overcome them.