Global and local influence-based social recommendation

Qinzhe Zhang, Jia Wu*, Hong Yang, Weixue Lu, Guodong Long, Chengqi Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

16 Citations (Scopus)


Social recommendation has been widely studied in recent years. Existing social recommendation models use various explicit pieces of social information as regularization terms, e.g., social links are considered as new constraints. However, social influence, an implicit source of information in social networks, is seldomly considered, even though it often drives recommendations in social networks. In this paper, we introduce a new global and local influence-based social recommendation model. Based on the observation that user purchase behaviour is influenced by both global influential nodes and the local influential nodes of the user, we formulate the global and local influence as an regularization terms, and incorporate them into a matrix factorization-based recommendation model. Experimental results on large data sets demonstrate the performance of the proposed method.

Original languageEnglish
Title of host publicationCIKM 2016
Subtitle of host publicationProceedings of the 25th ACM International on Conference on Information and Knowledge Management
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Electronic)9781450340731
Publication statusPublished - 24 Oct 2016
Externally publishedYes
Event25th ACM International Conference on Information and Knowledge Management, CIKM 2016 - Indianapolis, United States
Duration: 24 Oct 201628 Oct 2016


Conference25th ACM International Conference on Information and Knowledge Management, CIKM 2016
Country/TerritoryUnited States


  • Dual social influence
  • Social recommendation


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