articleFeb 1, 2011Closed access

Recommender systems with social regularization

Chinese University of Hong Kong · Microsoft (United States) · +1 more institution

Indexed incrossref

Abstract

Although Recommender Systems have been comprehensively analyzed in the past decade, the study of social-based recommender systems just started. In this paper, aiming at providing a general method for improving recommender systems by incorporating social network information, we propose a matrix factorization framework with social regularization. The contributions of this paper are four-fold: (1) We elaborate how social network information can benefit recommender systems; (2) We interpret the differences between social-based recommender systems and trust-aware recommender systems; (3) We coin the term Social Regularization to represent the social constraints on recommender systems, and we systematically…

Citation impact

1,658
total citations
FWCI
197.11
Percentile
100%
References
45
Citations per year

Authors

5

Topics & keywords

Keywords
  • Recommender system
  • Computer science
  • Matrix decomposition
  • Regularization (linguistics)
  • Artificial intelligence
  • Information retrieval
  • Machine learning
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