Exploiting local and global social context for recommendation

Jiliang Tang, Xia Hu, Huiji Gao, Huan Liu

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

129 Scopus citations

Abstract

With the fast development of social media, the information overload problem becomes increasingly severe and recommender systems play an important role in helping online users find relevant information by suggesting information of potential interests. Social activities for online users produce abundant social relations. Social relations provide an independent source for recommendation, presenting both opportunities and challenges for traditional recommender systems. Users are likely to seek suggestions from both their local friends and users with high global reputations, motivating us to exploit social relations from local and global perspectives for online recommender systems in this paper. We develop approaches to capture local and global social relations, and propose a novel framework LOCABAL taking advantage of both local and global social context for recommendation. Empirical results on real-world datasets demonstrate the effectiveness of our proposed framework and further experiments are conducted to understand how local and global social context work for the proposed framework.

Original languageEnglish (US)
Title of host publicationIJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence
Pages2712-2718
Number of pages7
StatePublished - Dec 1 2013
Event23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 - Beijing, China
Duration: Aug 3 2013Aug 9 2013

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Other

Other23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
CountryChina
CityBeijing
Period8/3/138/9/13

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ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Tang, J., Hu, X., Gao, H., & Liu, H. (2013). Exploiting local and global social context for recommendation. In IJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence (pp. 2712-2718). (IJCAI International Joint Conference on Artificial Intelligence).