Personalized Recommend System Combining User Interest and Social Circle

With the dawn of social network and its attractiveness, people are interested to share their experience, such as rating, reviews, etc. which helps to recommend the items of user interest. The potential growth of the internet results the use of social networks such as Face book, Twitter, linked-in etc. which produces huge amount of information (data), which leads to overwhelming. To overcome overwhelming, Personalized Recommendation System have been expansively used. In this paper, we discussed importance of Recommendation Systems, different methodologies and social factors, which influence Personalized Recommendation System. A deeper understanding of these social processes around user preference can help in creating better models of preference and lead to more effective personalization strategies. Key words— social networks, recommended system, interpersonal interest, association rule.