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Category-based filtering in Recommender systems for improved performance in dynamic domains
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0002-5562-1424
2002 (English)In: Lecture Notes in Computer Science: vol. 2347, Springer, 2002, 436-439 p.Chapter in book (Refereed)
Abstract [en]

In Recommender systems, collaborative filtering is the most commonly used technique. Although often successful, collaborative filtering encounters the latency problem in domains where items are frequently added, as the users have to review new items before they can be recommended. In this paper a novel approach to reduce the latency problem is proposed, based on category-based filtering and user stereotypes. © 2002 Springer-Verlag Berlin Heidelberg.

Place, publisher, year, edition, pages
Springer, 2002. 436-439 p.
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743 ; 2347
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-18683ISBN: 3540437371 (print)ISBN: 9783540437376 (print)OAI: oai:DiVA.org:mdh-18683DiVA: diva2:613473
Conference
2nd International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 2002, 29 May 2002 through 31 May 2002, Malaga
Note

2nd International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 2002; Malaga; 29 May 2002 through 31 May 2002

Available from: 2013-03-28 Created: 2013-03-28 Last updated: 2013-12-03Bibliographically approved

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Citation style
  • apa
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