Link prediction approach to collaborative filtering

Zan Huang, Xin Li, Hsinchun Chen

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

202 Citations (Scopus)

Abstract

Recommender systems can provide valuable services in a digital library environment, as demonstrated by its commercial success in book, movie, and music industries. One of the most commonly-used and successful recommendation algorithms is collaborative filtering, which explores the correlations within user-item interactions to infer user interests and preferences. However, the recommendation quality of collaborative filtering approaches is greatly limited by the data sparsity problem. To alleviate this problem we have previously proposed graph-based algorithms to explore transitive user-item associations. In this paper, we extend the idea of analyzing user-item interactions as graphs and employ link prediction approaches proposed in the recent network modeling literature for making collaborative filtering recommendations. We have adapted a wide range of linkage measures for making recommendations. Our preliminary experimental results based on a book recommendation dataset show that some of these measures achieved significantly better performance than standard collaborative filtering algorithms.

Original languageEnglish (US)
Title of host publicationProceedings of the ACM/IEEE Joint Conference on Digital Libraries
Pages141-142
Number of pages2
StatePublished - 2005
Event5th ACM/IEEE Joint Conference on Digital Libraries - Digital Libraries: Cyberinfrastructure for Research and Education - Denver, CO, United States
Duration: Jun 7 2005Jun 11 2005

Other

Other5th ACM/IEEE Joint Conference on Digital Libraries - Digital Libraries: Cyberinfrastructure for Research and Education
CountryUnited States
CityDenver, CO
Period6/7/056/11/05

Fingerprint

Collaborative filtering
Digital libraries
Recommender systems
Industry

Keywords

  • Collaborative filtering
  • Link prediction
  • Recommender system

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Huang, Z., Li, X., & Chen, H. (2005). Link prediction approach to collaborative filtering. In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (pp. 141-142)

Link prediction approach to collaborative filtering. / Huang, Zan; Li, Xin; Chen, Hsinchun.

Proceedings of the ACM/IEEE Joint Conference on Digital Libraries. 2005. p. 141-142.

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

Huang, Z, Li, X & Chen, H 2005, Link prediction approach to collaborative filtering. in Proceedings of the ACM/IEEE Joint Conference on Digital Libraries. pp. 141-142, 5th ACM/IEEE Joint Conference on Digital Libraries - Digital Libraries: Cyberinfrastructure for Research and Education, Denver, CO, United States, 6/7/05.
Huang Z, Li X, Chen H. Link prediction approach to collaborative filtering. In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries. 2005. p. 141-142
Huang, Zan ; Li, Xin ; Chen, Hsinchun. / Link prediction approach to collaborative filtering. Proceedings of the ACM/IEEE Joint Conference on Digital Libraries. 2005. pp. 141-142
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