Selecting relevant instances for efficient and accurate collaborative filtering

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2001, Pages 239-246

  Yu, Kai ^a   Xu, Xiaowei ^a   Ester, Martin ^a   Kriegel, Hans Peter ^a  

^a UNIVERSITY OF MUNICH   (Germany)

Author keywords

Collaborative filtering; Data Mining; Instance selection

Indexed keywords

ALGORITHMS; COMPUTER SUPPORTED COOPERATIVE WORK; CONSUMER PRODUCTS; DATA MINING; ELECTRONIC COMMERCE; INTERFACES (COMPUTER); INTERNET; LEARNING SYSTEMS; SALES;

COLLABORATIVE FILTERING;

DATABASE SYSTEMS;

EID: 0035747555     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/502624.502626     Document Type: Conference Paper

References (16)

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11. A review and empirical evaluation of feature weighting methods for a class of lazy learning algorithms
12. Reduction techniques for instance-based learning algorithms
13. Feature weighting and instance selection for collaborative filtering
14. Selecting typical instances in instance-based learning