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)
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| Status: |
Published |
| Creators/Authors: |
|
| 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: |
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| 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: |
08 Mar 2023 11:55 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/5963 |
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