Unifying collaborative and content-based filtering

Proceedings, Twenty-First International Conference on Machine Learning, ICML 2004

Volumn , Issue , 2004, Pages 65-72

  Basilico, Justin ^a   Hofmann, Thomas ^b  

^a Brown Univerity   (United States)

^b MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SYSTEMS; DATA PROCESSING; DATA REDUCTION; LEARNING SYSTEMS; MAPPING; MAPS; REGRESSION ANALYSIS;

CONTENT BASED FILTERING; DEMOGRAPHY; LEARNING ARCHITECTURE; REGRESSION PROBLEMS;

COMPUTER SUPPORTED COOPERATIVE WORK;

EID: 14344253490     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. Balabanovic, M., & Shoham, Y. (1997). Fab: Content-based, collaborative recommendation. Communications of the ACM, 40, 66-72.
2. Basu, C., Hirsh, H., & Cohen, W. W. (1998). Recommendation as classification: Using social and content-based information in recommendation. Proceedings of the 15th National Conference on Artificial Intelligence (pp. 714-720).
3. Billsus, D., & Pazzani, M. J. (1998). Learning collaborative information filters. Proceedings of the 15th International Conference on Machine Learning (pp. 46-54).
4. Breese, J. S., Heckerman, D., & Kardie, C. (1998). Empiricial analysis of predictive algorithms for collaborative filtering. Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (pp. 43-52).
5. Claypool, M., Gokhale, A., Miranda, T., Murnikov, P., Netes, D., &: Sartin, M. (1999). Combining content-based and collaborative filters in an online newspaper. Proceedings of ACM SIGIR Workshop on Recommender Systems.
6. Crammer, K., & Singer, Y. (2002). Pranking with ranking. Advances in Neural Information Processing Systems 14 (pp. 641-647).
7. Goldberg, D., Nichols, D., Oki, B., & Terry, D. (1992). Using collabrorative filtering to weave an information tapestry. Communications of the ACM, 35, 61-70.
8. Good, N., Schafer, J. B., Konstan, J. A., Borchers, A., Sarwar, B. M., Herlocker, J. L., & Riedl, J. (1999). Combining collaborative filtering with personal agents for better recommendations. Proceedings of the 16th National Conference on Artificial Intelligence (pp. 439-446).
9. Lang, K. (1995). NewsWeeder: Learning to filter netnews. Proceedings of the 12th International Conference on Machine Learning (pp. 331-339).
10. Melville, P., Mooney, R. J., & Nagarajan, R. (2002). Content-boosted collaborative filtering for improved recommendations. Proceedings of the 18th National Conference on Artificial Intelligence (pp. 187-192).
11. Mooney, R. J., & Roy, L. (2000). Content-based book recommending using learning for text categorization. Proceedings of the 5th ACM Conference on Digital Libraries (pp. 195-204).
12. Pazzani, M., Muramatsu, J., & Billsus, D. (1996). Syskill & Webert: Identifying interesting web sites. Proceedings of the 13th National Conference on Artificial Intelligence (pp. 54-61).
13. Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., &: Riedl, J. (1994). GroupLens: An open architecture for collaborative filtering of netnews. Proceedings of the ACM Conference on Computer Supported Cooperative Work (pp. 175-186).
14. Sarwar, B. M., Karypis, G., Konstan, J. A., & Reidl, J. (2001). Item-based collaborative filtering recommendation algorithms. Proceedings of the 10th International World Wide Web Conference (pp. 285-295).
15. Sarwar, B. M., Konstan, J. A., Borchers, A., Herlocker, J. L., Miller, B. N., & Riedl, J. (1998). Using filtering agents to improve prediction quality in the GroupLens research collaborative filtering system. Proceedings of the ACM Conference on Computer Supported Cooperative Work (pp. 345-354).
16. Schölkopf, B., & Smola, A. J. (2001). Learning with kernels. Cambridge, MA: MIT Press.
17. Shardanand, U., & Maes, P. (1995). Social information filtering: Algorithms for automating 'word of mouth'. Human Factors in Computing Systems ACM CHI (pp. 210-217).