Abstract: The latent growth of internet results the use of social Networks Such as Facebook, Linked In, MySpace or Twitter etc. which produce enormous amount of information .As a result users are faced with the problem of information overload, online Recommender System can be used to address the information overloaded problems by suggesting potentially interesting or useful items to users. Recent studies demonstrate that information from social networks can be dispirited to improve accuracy of recommendation. Online Recommender systems are intelligent tools that help on-line users to cultivated information overloaded. In this paper, we describe overview of online Recommender Systems, different techniques and social factors which influence Online Recommender System.
Keywords: Online Recommender system, Social network, Content based filtering, Collaborative filtering, Hybrid recommender system.