The Friend Recommendation System Based On Sina Web

Along with the development of information technology and the popularity of theInternet, micro-blog is becoming the main way of people’s daily communication andentertainment. In August2009, the Chinese web portal Sina launched "Sina micro-blog", itofficially entered the Chinese mainstream view online. As micro-blog is becoming moreand more hot among the Internet users, how to design a precise friend recommendationalgorithm and to expand the user’s network has become the hot topic of people It is alsothe research contents of this article.Firstly, the research status, cove idea,and study drawback are investigated. Then acollaborative filtering recommendation algorithm of micro-blog friends based on the user’sis designed. The algorithm includes interest, address, contacts, education job informationand integrated factors.Secondly, the similarity relation for the first four parts, is designed, Through therelationship formula algorithm similarity calculates the scores of the four parts, then setdifferent weights for each part, synthesizing four parts of similarity score calculates eachrecommendation results, according to the score screen, the top several similarity andsimilarity score will be displayed to the user respectively.Finally, Sina micro-blog friend recommendation system is established, the design ofsystem’s overall function is completed. The related database is designed for functionalmodule that signing in, personal home page, personal information, personal micro-blog,personal albums, paying close attention to fans, group management and friends home pageet al. The Sina micro-blog friend recommendation system is implemented, and the friendrecommendation algorithm is verified by the users’ data, thereby the objective that helpsusers to screen effective information rapidly is realized.