Optimizing Collaborative Filtering Recommender Systems

Collaborative filtering (CF) is the most successful recommendation technique, which has been used in a number of different applications. In traditional CF, the ratings of all items are equally weighted when similarity measure is calculated. But, if the importance of features (or items) is different respectively, feature weighting structure needs to be changed according to the importance of features. This paper presents a GA based feature weighting method. Through this weighting method, we can focus on the good items while removing bad ones or reducing their impacts.
Publisher
Springer Verlag (Germany)
Issue Date
2005
Citation

Advances in Web Intelligence, AWIC'2005 3-rd Atlantic Web Intelligence Conference , Lodz, Poland, 6-9 June 2005, pp. 313-319(7)

ISSN
1611-3349
DOI
10.1007/11495772_49
URI
http://hdl.handle.net/10203/3803
Link
http://www.springerlink.com/content/vv62apep484qhwmk/
Appears in Collection
KGSF-Conference Papers(학술회의논문)
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