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Reinforcing recommendation using implicit negative feedback

Lee, DH and Brusilovsky, P (2009) Reinforcing recommendation using implicit negative feedback. In: UNSPECIFIED.

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Abstract

Recommender systems have explored a range of implicit feedback approaches to capture users' current interests and preferences without intervention of users' work. However, current research focuses mostly on implicit positive feedback. Implicit negative feedback is still a challenge because users mainly target information they want. There have been few studies assessing the value of negative implicit feedback. In this paper, we explore a specific approach to employ implicit negative feedback and assess whether it can be used to improve recommendation quality. © 2009 Springer Berlin Heidelberg.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Lee, DHhyl12@pitt.eduHYL12
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 15 October 2009
Date Type: Publication
Journal or Publication Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume: 5535 L
Page Range: 422 - 427
Event Type: Conference
DOI or Unique Handle: 10.1007/978-3-642-02247-0_47
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 3642022464, 9783642022463
ISSN: 0302-9743
Related URLs:
Other ID: DOI: 10.1007/978-3-642-02247-0_47, ISBN: 978-3-642-02246-3
Date Deposited: 06 Jul 2011 18:51
Last Modified: 02 Jul 2020 15:56
URI: http://d-scholarship.pitt.edu/id/eprint/5963

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