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

C. He, Hanchao Li, Xiang Fei, A. Yang, Y. Tang, J. Zhu

Research output: Contribution to journalArticle

8 Citations (Scopus)
28 Downloads (Pure)

Abstract

Online social networks (OSNs) have become more and more popular and have attracted a great many users. Friend recommendation, which is one of the important services in OSN, can help users discover their interested friends and alleviate the problem of information overload. However, most of existing recommendation methods only consider either user link or content information and hence are not effective enough to provide high quality recommendations. In this paper, we propose a topic community-based method via Nonnegative Matrix Factorization (NMF). This method first applies joint NMF model to mine topic communities existing in OSN by combing link and content information. Then it computes user pairwise similarities and makes friends recommendation based on topic communities. Furthermore, this method can be implemented using the MapReduce distributed computing framework. Extensive experiments show that our proposed method not only has better recommendation performance than state-of-the-art methods but also has good scalability to deal with the problem of friend recommendation in large-sale OSNs. Moreover, the application case demonstrates that it can significantly improve friend recommendation service in the real world OSN.
Original languageEnglish
Article numbere3924
JournalConcurrency and Computation: Practice and Experience
Volume29
Issue number6
DOIs
Publication statusPublished - 21 Jul 2016

Fingerprint

Factorization
Social Networks
Recommendations
Distributed computer systems
Scalability
Sales
Non-negative Matrix Factorization
Information Content
Experiments
MapReduce
Overload
Distributed Computing
Community
Pairwise
Demonstrate
Experiment

Bibliographical note

This is the peer reviewed version of the following article: He, C, Li, H, Fei, X, Yang, A, Tang, Y & Zhu, J 2016, 'A topic community-based method for friend recommendation in large-scale online social networks' Concurrency and Computation: Practice and Experience, vol 29, no. 6, e3924, which has been published in final form at https://dx.doi.org/10.1002/cpe.3924 . This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

Keywords

  • online social networks
  • topic community mining
  • friend recommendation
  • nonnegative matrix factorization
  • MapReduce

Cite this

A topic community-based method for friend recommendation in large-scale online social networks. / He, C.; Li, Hanchao; Fei, Xiang; Yang, A.; Tang, Y.; Zhu, J.

In: Concurrency and Computation: Practice and Experience, Vol. 29, No. 6, e3924, 21.07.2016.

Research output: Contribution to journalArticle

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