Two-way cooperative prediction for collaborative filtering recommendations

Expert Systems with Applications

Volumn 36, Issue 3 PART 1, 2009, Pages 5353-5361

  Lee, Jong Seok ^a   Olafsson, Sigurdur ^a  

^a Iowa State University   (United States)

Author keywords

Collaborative filtering; Cooperation; Ensemble; Recommender systems

Indexed keywords

FORECASTING; MATRIX ALGEBRA; NUMERICAL METHODS; RECOMMENDER SYSTEMS;

AMOUNT OF INFORMATION; COLLABORATIVE FILTERING RECOMMENDATIONS; COOPERATION; COOPERATIVE PREDICTIONS; DIRECTIONAL INFORMATION; ENSEMBLE; NUMERICAL EXPERIMENTS; PREDICTION ACCURACY;

COLLABORATIVE FILTERING;

EID: 58349083876     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.06.106     Document Type: Article

References (13)

1. Breese, J. S., Heckerman, D., & Kadie, C. (1998). Empirical analysis of predictive algorithms for collaborative filtering, Microsoft research technical report, MSR-TR-98-12.
2. Breiman L. Bagging predictors. Machine Learning 24 (1996) 123-140
3. Goldberg D., Nichols D., Oki B., and Terry D. Using collaborative filtering to weave an information tapestry. Communications of the ACM 35 12 (1992) 61-70
4. Goldberg K., Roeder T., Gupta D., and Perkins C. Eigentaste: A constant time collaborative filtering algorithm. Information Retrieval Journal 4 2 (2001) 133-151
5. Han J., and Kamber M. Data mining: Concepts and techniques (2006), Morgan Kaufmann
6. Hosmer D.W., and Lemeshow S. Applied logistic regression (2000), John Wiley & Sons, New York
7. Kim T.-H., Ryu Y.-S., Park S.-I., and Yang S.-B. An improved recommendation algorithm in collaborative filtering. Lecture Notes in Computer Science 2455 (2002) 254-261
8. Lee J.-S., Jun C.-H., Lee J., and Kim S. Classification-based collaborative filtering using market basket data. Expert Systems with Applications 29 3 (2005) 700-704
9. Melville, P., Mooney, R., & Nagarajan, R. (2002). Content-boosted collaborative filtering for improved recommendations. In: Proceedings of the 18th national conference on artificial intelligence (AAAI-2002) (pp. 187-192). Edmonton, Canada: July.
10. Mild A., and Reutterer T. Collaborative filtering methods for binary market basket data analysis. Lecture Notes in Computer Science 2252 (2001) 302-313
11. Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th international world wide web conference (WWW10) (pp. 285-295). Hong Kong: May 1-5.
12. Ungar, L. H., & Foster, D. P. (1998). Clustering methods for collaborative filtering. Workshop on recommendation systems at the 15th national conference on artificial intelligence. Madison, Wisconsin: July.
13. Vucetic, S., & Obradovic, Z. (2000). A regression-based approach for scaling-up personalized recommender systems in E-commerce. In: Proceedings of the WEBKDD workshop on web mining for E-commerce - challenges and opportunities. Boston, Massachusetts: August.