期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：3
页码：6114
DOI：10.15680/IJIRCCE.2017.0503420
出版社：S&S Publications
摘要：Recommendation systems (RSs) are the most important part of Online Social Networks (OSNs) now adays. The main reason for the need of recommendation system is the exponential popularity of OSN. Although socialmedia provides a good and ease platform to share data and to communicate with friends, they also challenges its users.The challenge that OSN users face is “Information Overload”. The RS's can be modelled in such a way that, they canrecommend items/users to a target user based on the social data. Thus they will get personalized recommendations. Thebest way to get this type of recommendation is to incorporate trust information between the users. Most of the existingmodels work well with internet and computer based OSNs. But they will fail when used for mobile devices. Thehindrance to the performance of mobile OSN's are small screen, poor input, poor computational capabilities of mobiledevices, and user inconveniences to give feedback values. A better solution to these issues are an automatedrecommendation system for both mobile based and non-mobile based OSNs. So this work focuses to propose anautomated RS to recommend items/users based on social interaction data for both mobile and non-mobile based OSNs.
关键词：Recommendation systems; Social trust; Collaborative filtering. Online Social Networks.
