Collaborative users' brand preference mining across multiple domains from implicit feedbacks

Proceedings of the National Conference on Artificial Intelligence

Volumn 1, Issue , 2011, Pages 477-482

  Tang, Jian ^a   Yan, Jun ^b   Ji, Lei ^b   Zhang, Ming ^a   Guo, Shaodan ^c   Liu, Ning ^b   Wang, Xianfang ^d   Chen, Zheng ^b  

^a PEKING UNIVERSITY   (China)

^b MICROSOFT RESEARCH ASIA   (China)

^c HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^d MICROSOFT   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BROWSING BEHAVIOR; COLLABORATIVE FILTERING; COLLABORATIVE USERS; COLLECTIVE LEARNING; DATA SCARCITY; GENERAL LEARNING; IMPLICIT FEEDBACK; LATENT FACTOR; LEARNING PROCESS; LOG DATA; MULTIPLE DOMAINS; OPTIMIZATION CRITERIA; PERSONALIZED SERVICE; PREFERENCE LEARNING; PREFERENCE MINING; REAL-WORLD DATASETS; SINGLE DOMAINS; WEB BROWSING;

ARTIFICIAL INTELLIGENCE; BEHAVIORAL RESEARCH; OPTIMIZATION; USER INTERFACES;

FEEDBACK;

EID: 80055044193     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Breese J.; Heckerman D.; and Kadie C. 1998. Empirical analysis of predictive algorithms for collaborative filtering. In UAI'98, 43-52.
2. Bell R.; and Koren Y. 2007. Scalable collaborative filtering with jointly derived neighborhood interpolation weights. In ICDM'07,43-52.
3. Cao B.; Liu N.; and Q. Yang. 2010. Transfer Learning for Collective Link Prediction in Multiple Heterogeneous Domains. In ICML'10,159-166.
4. Holland S.; Ester M.; and Kiebling W. 2003. Preference mining: a novel approach mining user preferences for personalized applications. In PKDD'03, 204-216.
5. Hu Y.; Koren Y.; and Volinsky C. 2008. Collaborative filtering for implicit feedback datasets. In ICDM'08,263-272.
6. Jung S.; Hong J. H.; and Kim T. S. 2005. A statistical model for user preference. IEEE TKDE, 2005, 834-843.
7. Li B.; Yang Q.; and Xue X. 2009. Can movies and books collaborate? Cross-domain collaborative filtering for sparsity reduction. In IJCAI'09, 2052-2057.
8. Li B.; Yang Q.; and Xue X. 2009. Transfer learning for collaborative filtering via a rating-matrix generative model. In ICML'09, 617-624.
9. Pan R.; Zhou Y.; Cao B.; Liu N.; Lukose R.; Scholz M.; and Yang Q. 2008. One-class collaborative filtering. In ICDM'08, 502-511.
10. Rasmussen C.; and Williams C. 2006. Gaussian processes for machine learning. The MIT Press, 2006.
11. Rendle S.; Freudenthaler C.; Gantner Z.; and Schmidt-Thieme L. 2009. BPR: Bayesian personalized ranking from implicit feedback. In UAI'09, 452-461.
12. Singh A. and Gordon G. J. 2008. Relational learning via collective matrix factorization. In KDD'08, 650-658.
13. Xu Z.; Kersting K.; and Tresp V. 2009. Multi-relational learning with Gaussian processes. In IJCAI'09, 1309-1314.
14. Zhang Y.; Cao B.; and Yeung D. 2010. Multi-domain collaborative filtering. In UAI'2010, 725-732.