Improving recommender systems by incorporating social contextual information

ACM Transactions on Information Systems

Volumn 29, Issue 2, 2011, Pages

  Ma, Hao ^a   Zhou, Tom Chao ^a   Lyu, Michael R ^a   King, Irwin ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Collaborative filtering; Matrix factorization; Recommender systems; Social network; Tags

Indexed keywords

COLLABORATIVE FILTERING; COMPLEXITY ANALYSIS; CONTEXTUAL INFORMATION; DATA SPARSITY; DATA SPARSITY PROBLEMS; EXPONENTIAL GROWTH; FACTOR ANALYSIS; LARGE DATASETS; MATRIX FACTORIZATIONS; ONLINE USERS; PREDICTION ACCURACY; RESEARCH CHALLENGES; SOCIAL NETWORK; SOCIAL NETWORKS; STATE-OF-THE-ART APPROACH; TAGS; USER-ITEM MATRIX; WEB APPLICATION;

COMPUTER AIDED NETWORK ANALYSIS; FACTORIZATION; RECOMMENDER SYSTEMS; USER INTERFACES;

MATRIX ALGEBRA;

EID: 80051490270     PISSN: 10468188     EISSN: 15582868     Source Type: Journal    
DOI: 10.1145/1961209.1961212     Document Type: Article

References (49)

1. BANERJEE, S. AND RAMANATHAN, K. 2008. Collaborative filtering on skewed datasets. In Proceedings of the 17th International Conference on World Wide Web (WWW'08). 1135-1136.
2. BEDI, P., KAUR, H., AND MARWAHA, S. 2007. Trust based recommender system for semantic web. In Proceedings of International Joint Conferences on Artificial Intelligence (IJCAI'07). 2677-2682.
3. BELL, R., KOREN, Y., AND VOLINSKY, C. 2007. Modeling relationships at multiple scales to improve accuracy of large recommender systems. In Proceedings of the International SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'07). 95-104. (Pubitemid 350229196)
4. BREESE, J. S., HECKERMAN, D., AND KADIE, C. 1998a. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI'98). Morgan Kaufmann, San Francisco, CA, 43-52.
5. BREESE, J. S., HECKERMAN, D., AND KADIE, C. 1998b. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI'98).
6. CANNY, J. 2002. Collaborative filtering with privacy via factor analysis. In Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'02). 238-245.
7. CAO, B., SUN, J.-T., WU, J., YANG, Q., AND CHEN, Z. 2008. Learning bidirectional similarity for collaborative filtering. In Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases Part I (ECMLPKDD'08). 178-194.
8. DAS, A. S., DATAR, M., GARG, A., AND RAJARAM, S. 2007. Google news personalization: Scalable online collaborative filtering. In Proceedings of the 16th International Conference on World Wide Web (WWW'07). 271-280. (Pubitemid 47582257)
9. DESHPANDE, M. AND KARYPIS, G. 2004. Item-Based top-n recommendation. ACM Trans. Inf. Syst. 22, 1, 143-177.
10. DUECK, D. AND FREY, B. 2004. Probabilistic sparse matrix factorization. Tech. rep. PSI TR 2004-023. Department of Computer Science, University of Toronto.
11. GAO, B., LIU, T.-Y., ZHENG, X., CHENG, Q.-S., AND MA, W.-Y. 2005. Consistent bipartite graph copartitioning for star-structured high-order heterogeneous data co-clustering. In Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery in Data Mining (KDD'05). 41-50. (Pubitemid 43218266)
12. GUHA, R., KUMAR, R., RAGHAVAN, P., AND TOMKINS, A. 2004. Propagation of trust and distrust. In Proceedings of the 13th International Conference on World Wide Web (WWW'04). 403-412. (Pubitemid 40752775)
13. HERLOCKER, J. L., KONSTAN, J. A., BORCHERS, A., AND RIEDL, J. 1999. An algorithmic framework for performing collaborative filtering. In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'99). 230-237.
14. HERLOCKER, J. L., KONSTAN, J. A., TERVEEN, L. G., AND RIEDL, J. T. 2004. Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22, 1, 5-53.
15. HEYMANN, P., KOUTRIKA, G., AND GARCIA-MOLINA, H. 2008. Can social bookmarking improve web search? In Proceedings of the International Conference on Web Search and Web Data Mining (WSDM'08). 195-206.
16. HOFMANN, T. 2003. Collaborative filtering via gaussian probabilistic latent semantic analysis. In Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Informaion Retrieval (SIGIR'03). 259-266.
17. HOFMANN, T. 2004. Latent semantic models for collaborative filtering. ACM Trans. Inf. Syst. 22, 1, 89-115.
18. HUANG, Z., CHEN, H., AND ZENG, D. 2004. Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering. ACM Trans. Inf. Syst. 22, 1, 116-142.
19. JIN, R., CHAI, J. Y., AND SI, L. 2004. An automatic weighting scheme for collaborative filtering. In Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'04). 337-344.
20. KOHRS, A. AND MERIALDO, B. 1999. Clustering for collaborative filtering applications. In Proceedings of the International Conference on Computational Intelligence for Modeling Control and Automation (CIMCA).
21. KOREN, J., ZHANG, Y., AND LIU, X. 2008. Personalized interactive faceted search. In Proceeding of the 17th International Conference on World Wide Web (WWW'08). 477-486.
22. KOREN, Y. 2008. Factorization meets the neighborhood: a multifaceted collaborative filtering model. In Proceedings of the International SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'08). 426-434.
23. KURUCZ, M., BENCZUR, A. A., AND CSALOGANY, K. 2007. Methods for large scale svd with missing values. In Proceedings of the KDD Cup and Workshop.
24. LEE, D. D. AND SEUNG, H. S. 1999. Learning the parts of objects by non-negative matrix factorization. Nature 401, 6755, 788-791.
25. LI, X., GUO, L., AND ZHAO, Y. E. 2008. Tag-based social interest discovery. In Proceedings of the 17th International Conference on World Wide Web (WWW'08). 675-684.
26. LINDEN, G., SMITH, B., AND YORK, J. 2003. Amazon. com recommendations: Item-to-Item collaborative filtering. IEEE Internet Comput., 76-80.
27. LONG, B., ZHANG, Z. M., WÚ, X., AND YU, P. S. 2006. Spectral clustering for multi-type relational data. In Proceedings of the 23rd International Conference on Machine Learning (ICML'06). 585-592.
28. MA, H., KING, I., AND LYU, M. R. 2007. Effective missing data prediction for collaborative filtering. In Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'07). 39-46. (Pubitemid 350164942)
29. MA, H., YANG, H., LYU, M. R., AND KING, I. 2008. Sorec: Social recommendation using probabilistic matrix factorization. In Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM'08). 931-940.
30. MARLIN, B. 2004. Modeling user rating profiles for collaborative filtering. In Advances in Neural Information Processing Systems, Vol. 16, S. Thrun, L. Saul, and B. Schölkopf Eds., MIT Press, Cambridge, MA.
31. MASSA, P. AND AVESANI, P. 2004. Trust-Aware collaborative filtering for recommender systems. In Proceedings of CoopIS/DOA/ODBASE Conference. 492-508. (Pubitemid 39750452)
32. RAMAGE, D., HEYMANN, P., MANNING, C. D., AND GARCIA-MOLINA, H. 2009. Clustering the tagged web. In Proceedings of the 2nd ACM International Conference on Web Search and Data Mining (WSDM'09). 54-63.
33. RENNIE, J. D. M. AND SREBRO, N. 2005. Fast maximum margin matrix factorization for collaborative prediction. In Proceedings of the 22nd International Conference on Machine Learning (ICML'05).
34. RESNICK, P., IACOVOU, N., SUCHAK, M., BERGSTROM, P., AND RIEDL, J. 1994. Grouplens: An open architecture for collaborative filtering of netnews. In Proceedings of ACM Conference on Computer Supported Cooperative Work.
35. SALAKHUTDINOV, R. AND MNIH, A. 2008a. Bayesian probabilistic matrix factorization using markov chain monte carlo. In Proceedings of the 25th International Conference on Machine Learning (ICML'08).
36. SALAKHUTDINOV, R. AND MNIH, A. 2008b. Probabilistic matrix factorization. In Advances in Neural Information Processing Systems, Vol. 20.
37. SALAKHUTDINOV, R., MNIH, A., AND HINTON, G. 2007. Restricted boltzmann machines for collaborative filtering. In Proceedings of the 24th International Conference on Machine Learning (ICML'07). 791-798.
38. SARWAR, B., KARYPIS, G., KONSTAN, J., AND REIDL, J. 2001. Item-Based collaborative filtering recommendation algorithms. In Proceedings of the 10th International Conference on World Wide Web (WWW'01). 285-295.
39. SCHENKEL, R., CRECELIUS, T., KACIMI, M., MICHEL, S., NEUMANN, T., PARREIRA, J. X., AND WEIKUM, G. 2008. Efficient top-k querying over social-tagging networks. In Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'08). 523-530.
40. SEN, S., LAM, S. K., RASHID, A. M., COSLEY, D., FRANKOWSKI, D., OSTERHOUSE, J., HARPER, F. M., AND RIEDL, J. 2006. Tagging, communities, vocabulary, evolution. In Proceedings of the 20th Anniversary Conference on Computer Supported Cooperative Work (CSCW'06). 181-190. (Pubitemid 47112406)
41. SI, L. AND JIN, R. 2003. Flexible mixture model for collaborative filtering. In Proceedings of the 20th International Conference on Machine Learning (ICML'03).
42. SINGLA, P. AND RICHARDSON, M. 2008. Yes, there is a correlation - From social networks to personal behavior on the web. In Proceedings of the 17th International Conference on World Wide Web (WWW'08). 655-664.
43. SINHA, R. R. AND SWEARINGEN, K. 2001. Comparing recommendations made by online systems and friends. In Proceedings of the DELOS Workshop: Personalisation and Recommender Systems in Digital Libraries.
44. SONG, Y., ZHUANG, Z., LI, H., ZHAO, Q., LI, J., LEE, W.-C., AND GILES, C. L. 2008. Real-Time automatic tag recommendation. In Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'08). 515-522.
45. SREBRO, N. AND JAAKKOLA, T. 2003. Weighted low-rank approximations. In Proceedings of the 20th International Conference on Machine Learning (ICML'03). 720-727.
46. ZHANG, Y. AND KOREN, J. 2007. Efficient bayesian hierarchical user modeling for recommendation system. In Proceedings of the Annual ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'07). 47-54. (Pubitemid 350164943)
47. ZHOU, D., SCHOLKOPF, B., AND HOFMANN, T. 2005. Semi-Supervised learning on directed graphs. In Advances in Neural Information Processing Systems, Vol. 17.
48. ZHOU, D., ZHU, S., YU, K., SONG, X., TSENG, B. L., ZHA, H., AND GILES, C. L. 2008. Learning multiple graphs for document recommendations. In Proceedings of the 17th International Conference on World Wide Web (WWW'08). 141-150.
49. ZHU, S., YU, K., AND GONG, Y. 2008. Predictive matrix-variate t models. In Advances in Neural Information Processing Systems, Vol. 20, J. Platt and S. Roweis Eds., MIT Press, Cambridge, MA, 1721-1728.