Collaborative filtering: Special case in predictive analysis

International Journal of Computer Mathematics

Volumn 82, Issue 1, 2005, Pages 1-11

  Tout, K ^a   Evans, D J ^b   Yakan, A ^c  

^a LEBANESE UNIVERSITY   (Lebanon)

^b NOTTINGHAM TRENT UNIVERSITY   (United Kingdom)

^c Jinan University Of Lebanon   (Lebanon)

Author keywords

Bayesian networks; Collaborative filtering; Expectation maximization; Memory based vs. model based algorithms; Pearson correlation; Recommender systems; Vector similarity

Indexed keywords

ALGORITHMS; CORRELATION METHODS; DATA TRANSFER; DECISION MAKING; INTERNET; USER INTERFACES;

BAYESIAN NETWORKS; COLLABORATIVE FILTERING; EXPECTATION MINIMIZATION; PEARSON CORRELATIONS; RECOMMENDER SYSTEMS; VECTOR SIMILARITY;

COMPUTER SUPPORTED COOPERATIVE WORK;

EID: 27944488722     PISSN: 00207160     EISSN: 10290265     Source Type: Journal    
DOI: 10.1080/00207160412331290702     Document Type: Article

References (4)

1. Breese, J., Heckerman, D. and Kadie, C., 1998, Empirical analysis of predictive algorithms for collaborative filtering, Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July.
2. Han, J. and Kamber, M., 2001, Data Mining: Concepts and Techniques (San Francisco, CA: Morgan Kaufmann).
3. Microsoft Anonymous Web Data, 1999, http://kdd.ics.uci.edu/databases/ msweb/msweb.html
4. Witten, I.H. and Frank, E., 2000, Data Mining Practical Machine Learning Tools and Techniques with Java Implementations (San Francisco, CA: Morgan Kaufmann).