A user recommendation scheme based on similar community and node role division in social network
In view of current research on user recommendation mainly considering similarity of node pair and ignoring role level difference of users,we introduce a new way based on similar community and node role division.At first,relying on the similarity of node pair,we put forward a method to calculate the similarity of community pairs from two perspectives:community structure and attributes of users.Secondly,according to the measurement to external and internal tightness of every node in community,we analyze the users’social influence and divide them into different roles in order to recommend friends discriminatively.Finally,we select Sina Weibo data to verify our method.Experiment results show that the scheme performs well and is suitable for user recommendation where there are communities in the social network and users can be divided into roles of different levels.
similar communitynode roleuser recommendationsocial network
国家科技期刊平台
NSTL
万方数据
维普
