A topic community-based method for friend recommendation in large-scale online social networks-Reference-Cited by-同舟云学术

A topic community-based method for friend recommendation in large-scale online social networks

Published:2016-07-21 Issue:6 Volume:29 Page:e3924
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat.: Pract. Exper.

Author:

He Chaobo¹²,Li Hanchao³,Fei Xiang³,Yang Atiao⁴,Tang Yong²,Zhu Jia²

Affiliation:

1. School of Information Science and Technology; ZhongKai University of Agriculture and Engineering; Guangzhou 510225 China

2. School of Computer; South China Normal University; Guangzhou 510631 China

3. Department of Computing; Coventry University; Coventry CV1 5FB UK

4. School of Mathematics and Computer Science; Guizhou Normal University; Guiyang 550001 China

Funder

National High-Technology Research

Development Program (“863” Program) of China

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province, China

Science and Technology Support Program of Guangdong Province, China

Open Research Fund from Guangzhou Key Lab on Cloud Security and Assessment

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/cpe.3924/fullpdf

Reference37 articles.

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2. Xie X Potential friend recommendation in online social network Proceedings of 3rd IEEE/ACM International Conference on Cyber, Physical and Social Computing Hangzhou, China 2010 831 835

3. Naruchitparames J Gunes MH Lou SJ Friend recommendations in social networks using genetic algorithms and network topology Proceedings of 2011 IEEE Congress on Evolutionary Computation New Orleans, USA 2011 2207 2214

4. Tang Q Hartel P Poster: privacy-preserving profile similarity computation in online social networks Proceedings of the 18th ACM conference on Computer and Communications Security Chicago, USA 2011 793 796

5. Interest-driven private friend recommendation;Samanthula;Knowledge and Information Systems,2015

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