A incremental clustering method for preference similar users

Abstract

With the development of social networks, services and applications based on social networks have become more and more abundant. While providing convenient services and applications for users, the providers have also accumulated many user information. How to use information to provide users with accurate and high-quality services is an issue that needs to be solved. The division of user groups is the basis for solving this problem. User preference is the important information for division, and clustering is the means of division. In order to solve the problem of user group partition efficiency in big data environment, this paper presents a new user preference similarity calculation method. On this basis, initial clustering based on Fast Unfolding algorithm and how to determine the attribution classes of update nodes based on the initial clustering results, the clustering method of incrementally preferring similar users is proposed. Experimental results show that the proposed algorithm greatly improves the division efficiency of user groups.