Computer Science ›› 2018, Vol. 45 ›› Issue (3): 218-222.doi: 10.11896/j.issn.1002-137X.2018.03.034

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Friend Recommendation Method Based on Users’ Latent Features in Social Networks

XIAO Ying-yuan and ZHANG Hong-yu   

  • Online:2018-03-15 Published:2018-11-13

Abstract: With the popularity of social networks,such as Facebook,Twitter and Microblog,friend recommendation systems have gradually become an important part of social networks.Friend recommendation systems effectively expand the scale of user’s social circle and improve user’s social experience by actively recommending new potential friends for users,thus receiving widespread attention.However,how to personalize the user’s needs and recommend realfriends to users has been one of the difficulties for personalized friend recommendation.This paper presented a social networking friend recommendation method based on users’ latent features,called SNFRLF.SNFRLF first leverages latent factor model to mine users’ latent features,and then calculates the similarity between users by means of users’ latent features.Finally,the similarity is introduced into the random walk model to get a recommended list.The experimental results show that the proposed method significantly outperforms the existing friend recommendation methods.

Key words: Friend recommendation,Social network,Latent factor model,Random walk

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