Research on the Method of Friends Recommendation in Mobile Social Network Based on Multidimensional Similarity

Aiming at the issue of friend recommendation in social network, a friend recommendation method based on multi dimensional similarity is proposed. Compared with the existing methods, it is no longer limited to a single dimension of matching information, but from three dimensions of interest, time, and space to judge the similarity of users in different dimensionality, then it uses the similarity to do comprehensive evaluation to recommend friends to the target users. Experimental studies have shown that the precision rate of recommended results is close to 70 percent, and the checking efficiency rate is close to 60 percent when the method is applied to the recommendation service of mobile social network. The performance of this method is much higher than the friend recommended method based on single dimension and can be applied to a variety of characteristics of the mobile social network.

[1]  Xin Wang,et al.  Friend recommendation with content spread enhancement in social networks , 2015, Inf. Sci..

[2]  Scott Counts,et al.  Group-Based Mobile Messaging in Support of the Social Side of Leisure , 2007, Computer Supported Cooperative Work (CSCW).

[3]  Noël Crespi,et al.  Alike people, alike interests? Inferring interest similarity in online social networks , 2015, Decis. Support Syst..

[4]  Aniket Kittur,et al.  Bridging the gap between physical location and online social networks , 2010, UbiComp.

[5]  Junliang Chen,et al.  Recommending friends instantly in location-based mobile social networks , 2014 .

[6]  Chang Xu-liang.  Collaborative filtering recommendation algorithm based on user clustering of item attributes , 2010 .

[7]  Y Wang.  Social Circle-Based Algorithm for Friend Recommendation in Online Social Networks , 2014 .

[8]  Xingshe Zhou,et al.  Hybrid SN: Interlinking Opportunistic and Online Communities to Augment Information Dissemination , 2012, 2012 9th International Conference on Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Trusted Computing.

[9]  Guanling Chen,et al.  Multi-layered friendship modeling for location-based Mobile Social Networks , 2009, 2009 6th Annual International Mobile and Ubiquitous Systems: Networking & Services, MobiQuitous.

[10]  Jie Liu,et al.  A link prediction algorithm based on label propagation , 2016, J. Comput. Sci..

[11]  Wei Jiang,et al.  Interest-driven private friend recommendation , 2013, Knowledge and Information Systems.