Time-dependent models in collaborative filtering based recommender system

Proceedings - 2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009

Volumn 1, Issue , 2009, Pages 450-457

  Xiang, Liang ^a   Yang, Qing ^a  

^a INSTITUTE OF AUTOMATION   (China)

Author keywords

Collaborative filtering; Netflix; Temporal effects; Time dependent models

Indexed keywords

COLLABORATIVE FILTERING; NETFLIX; PREDICTION ACCURACY; SIMPLE METHOD; TEMPORAL EFFECTS; TEMPORAL FEATURES; TIME EFFECT; TIME INFORMATION; TIME-DEPENDENT MODELS;

RECOMMENDER SYSTEMS;

EID: 84856813600     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WI-IAT.2009.78     Document Type: Conference Paper

References (25)

1. "Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions," IEEE Trans. on Knowl. and Data Eng., vol. 17, no. 6, pp. 734- 749, 2005, member-Adomavicius, Gediminas and Member- Tuzhilin, Alexander.
2. G. Linden, B. Smith, and J. York, "Amazon.com recommendations: item-to-item collaborative filtering," Internet Computing, IEEE, vol. 7, no. 1, pp. 76-80, Jan/Feb 2003.
3. A. S. Das, M. Datar, A. Garg, and S. Rajaram, "Google news personalization: scalable online collaborative filtering," WWW '07: Proceedings of the 16th international conference on World Wide Web, pp. 271-280, 2007.
4. S.-T. Park and D. M. Pennock, "Applying collaborative filtering techniques to movie search for better ranking and browsing," KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 550-559, 2007.
5. J. Bennet and S. Lanning, "The netflix prize," KDD Cup and Workshop, 2007.
6. P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl, "Grouplens: an open architecture for collaborative filtering of netnews," CSCW '94: Proceedings of the 1994 ACM conference on Computer supported cooperative work, pp. 175-186, 1994.
7. J. A. Konstan, B. N. Miller, D. Maltz, J. L. Herlocker, L. R. Gordon, and J. Riedl, "Grouplens: applying collaborative filtering to usenet news," Commun. ACM, vol. 40, no. 3, pp. 77-87, 1997.
8. B. Sarwar, G. Karypis, J. Konstan, and J. Reidl, "Item-based collaborative filtering recommendation algorithms," WWW '01: Proceedings of the 10th international conference on World Wide Web, pp. 285-295, 2001.
9. M. Deshpande and G. Karypis, "Item-based top-n recommendation algorithms," ACM Trans. Inf. Syst., vol. 22, no. 1, pp. 143-177, 2004.
10. T. Hofmann and J. Puzicha, "Latent class models for collaborative filtering," IJCAI '99: Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, pp. 688-693, 1999.
11. T. Hofmann, "Latent semantic models for collaborative filtering," ACM Trans. Inf. Syst., vol. 22, no. 1, pp. 89-115, 2004.
12. B. Mehta, T. Hofmann, and W. Nejdl, "Robust collaborative filtering," RecSys '07: Proceedings of the 2007 ACM conference on Recommender systems, pp. 49-56, 2007.
13. J. D. M. Rennie and N. Srebro, "Fast maximum margin matrix factorization for collaborative prediction," ICML '05: Proceedings of the 22nd international conference on Machine learning, pp. 713-719, 2005.
14. N. Srebro and T. Jaakkola, "Weighted low rank approximation," 20th International Conference on Machine Learning, 2003.
15. R. M. Bell and Y. Koren, "Scalable collaborative filtering with jointly derived neighborhood interpolation weights," ICDM '07: Proceedings of the 2007 Seventh IEEE International Conference on Data Mining, pp. 43-52, 2007.
16. Y. Ding and X. Li, "Time weight collaborative filtering," pp. 485-492, 2005.
17. R. Bell, Y. Koren, and C. Volinsky, "The bellkor solution to the netflix prize," Technical report, AT&T Labs, 2007.
18. Y. K. C. V. Robert Bell, "The bellkor 2008 solution to the netflix prize," Technical report, AT&T Labs, 2008.
19. Y. Koren, "Factorization meets the neighborhood: a multifaceted collaborative filtering model," KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 426-434, 2008.
20. D. G. Ken Goldberg, Theresa Roeder and C. Perkins, "Eigentaste: A constant time collaborative filtering algorithm," Information Retrieval.
21. G. Takács, I. Pilászy, B. Németh, and D. Tikk, "Major components of the gravity recommendation system," SIGKDD Explor. Newsl., vol. 9, no. 2, pp. 80-83, 2007.
22. A. Töscher and M. Jahrer, "The bigchaos solution to the netflix prize 2008," 2008.
23. G. Takács, I. Pilászy, B. Németh, and D. Tikk, "On the gravity recommendation system.
24. Y. Koren, "Factor in the neighbors : Scalable and accurate collaborative filtering," 2008.
25. A. Paterek, "Improving regularized singular value decomposition for collaborative filtering," 2007, pp. 39-42.