Abstract
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 language | English |
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Title of host publication | CIKM 2016 |
Subtitle of host publication | Proceedings of the 25th ACM International on Conference on Information and Knowledge Management |
Place of Publication | New York, NY |
Publisher | Association for Computing Machinery |
Pages | 1917-1920 |
Number of pages | 4 |
ISBN (Electronic) | 9781450340731 |
DOIs | |
Publication status | Published - 24 Oct 2016 |
Externally published | Yes |
Event | 25th ACM International Conference on Information and Knowledge Management, CIKM 2016 - Indianapolis, United States Duration: 24 Oct 2016 → 28 Oct 2016 |
Conference
Conference | 25th ACM International Conference on Information and Knowledge Management, CIKM 2016 |
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Country/Territory | United States |
City | Indianapolis |
Period | 24/10/16 → 28/10/16 |
Keywords
- Dual social influence
- Social recommendation