Research on Collaborative Filtering Algorithm in Microblogging Recommendation

Abstract

The personalized demand of users in social networks is an important factor of the user satisfaction. Integrated user microblog content and user interaction information, introduce the concept of interest similarity and interaction trust. This paper proposes an improved collaborative filtering recommendation algorithm. Computing user interest similarity and user interaction trust, linear fitting of the 2 sub similarity. It can calculate the total similarity between the users of micro-blog personalized recommendation. The experimental result shows that the new algorithm can effectively improve the accuracy, quality and user satisfaction of recommendation system in social networks.