Circle-based recommendation in online social networks

Xiwang Yang, Harald Steck, Yong Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Online social network information promises to increase recommendation accuracy beyond the capabilities of purely rating/feedback-driven recommender systems (RS). As to better serve users' activities across different domains, many online social networks now support a new feature of "Friends Circles", which refines the domain-oblivious "Friends" concept. RS should also benefit from domain-specific "Trust Circles". Intuitively, a user may trust different subsets of friends regarding different domains. Unfortunately, in most existing multi-category rating datasets, a user's social connections from all categories are mixed together. This paper presents an effort to develop circle-based RS. We focus on inferring category-specific social trust circles from available rating data combined with social network data. We outline several variants of weighting friends within circles based on their inferred expertise levels. Through experiments on publicly available data, we demonstrate that the proposed circle-based recommendation models can better utilize user's social trust information, resulting in increased recommendation accuracy.

Original languageEnglish (US)
Title of host publicationKDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Pages1267-1275
Number of pages9
DOIs
StatePublished - 2012
Event18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012 - Beijing, China
Duration: Aug 12 2012Aug 16 2012

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Other

Other18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012
CountryChina
CityBeijing
Period8/12/128/16/12

Keywords

  • collaborative filtering
  • friends circles
  • online social networks
  • recommender systems

ASJC Scopus subject areas

  • Software
  • Information Systems

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  • Cite this

    Yang, X., Steck, H., & Liu, Y. (2012). Circle-based recommendation in online social networks. In KDD'12 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 1267-1275). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). https://doi.org/10.1145/2339530.2339728