期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2016
卷号：5
期号：11
页码：20033
DOI：10.15680/IJIRSET.2016.0511079
出版社：S&S Publications
摘要：Online Social Networks (OSNs) have grown a lot from the past and now it is becoming more and morepopular in today’s life. The main problem facing by today’s networks is “information overloading”. A solution to thisproblem is a good recommendation system. It automatically suggests items to a user that he/she is having interest in it.To improve the accuracy and precision of recommendation systems, we have to incorporate information from socialnetwork. If so, the system will automatically monitors the social activities of users and ranks other users andrecommends items/users to a target user based on this information. We provide a brief idea about the tasks ofrecommender system and how the concept of social interaction can be utilised to make recommendation. Here we makea comparative study of various recommendation systems which uses social data for normal users and mobile users. Wealso discuss about the traditional recommendation systems that do not uses social information also.
关键词：Recommendation systems; Social trust; Collaborative filtering. Online Social Networks.
