| Personalized interactive faceted search |
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International World Wide Web Conference
archive
Proceeding of the 17th international conference on World Wide Web
table of contents
Beijing, China
SESSION: Search: applications
table of contents
Pages 477-486
Year of Publication: 2008
ISBN:978-1-60558-085-2
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Authors
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Jonathan Koren
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University of California, Santa Cruz, Santa Cruz, CA, USA
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Yi Zhang
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University of California, Santa Cruz, Santa Cruz, CA, USA
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Xue Liu
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McGill University, Montreal, PQ, Canada
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ABSTRACT
Faceted search is becoming a popular method to allow users to interactively search and navigate complex information spaces. A faceted search system presents users with key-value metadata that is used for query refinement. While popular in e-commerce and digital libraries, not much research has been conducted on which metadata to present to a user in order to improve the search experience. Nor are there repeatable benchmarks for evaluating a faceted search engine. This paper proposes the use of collaborative filtering and personalization to customize the search interface to each user's behavior. This paper also proposes a utility based framework to evaluate the faceted interface. In order to demonstrate these ideas and better understand personalized faceted search, several faceted search algorithms are proposed and evaluated using the novel evaluation methodology.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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A. Bandura. Social Learning Theory. General Learning Press, 1977.
|
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2
|
|
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3
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Z. Chen, L. Wenyin, F. Lin, P. Xiao, L. Yin, B. Lin, and W.-Y. Ma. User modeling for building personalized web assistants. In Proceedings of the 11th International World Wide Web Conference (WWW '02), 2002.
|
| |
4
|
GroupLens. Movielens. http://www.grouplens.org/taxonomy/term/14/, 2006.
|
 |
5
|
|
| |
6
|
M. A. Hearst. User interfaces and visualization. In R. Baeza-Yates and B. Ribeiro-Neto, editors, Modern Information Retrieval, chapter 10, pages 257--323. ACM Press, New York, NY, USA, 1999.
|
| |
7
|
H. Inan. Search Analytics: A Guide to Analyzing and Optimizing Website Search Engines. Book Surge Publishing, 2006.
|
| |
8
|
Internet Movie Database Inc. Internet movie database. http://www.imdb.com/interfaces/, 2006.
|
 |
9
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Joseph A. Konstan , Bradley N. Miller , David Maltz , Jonathan L. Herlocker , Lee R. Gordon , John Riedl, GroupLens: applying collaborative filtering to Usenet news, Communications of the ACM, v.40 n.3, p.77-87, March 1997
[doi> 10.1145/245108.245126]
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 |
10
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Rui Li , Shenghua Bao , Yong Yu , Ben Fei , Zhong Su, Towards effective browsing of large scale social annotations, Proceedings of the 16th international conference on World Wide Web, May 08-12, 2007, Banff, Alberta, Canada
[doi> 10.1145/1242572.1242700]
|
| |
11
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N. Miller and J. Dollard. Social Learning and Imitation. Yale University Press, 1941.
|
| |
12
|
D. Mladenić. Personal web watcher: Design and implentation. Technical report, J. Stefan Institute, Department for Intelligent Systems, Ljubljana, Slovenia, 1998.
|
| |
13
|
Netflix. Netflix prize. http://www.netflixprize.com, 2006.
|
 |
14
|
|
 |
15
|
|
| |
16
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D. Tunkelang. Dynamic category sets: An approach for faceted search. In ACM SIGIR '06 Workshop on Faceted Search, August 2006.
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17
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Ka-Ping Yee , Kirsten Swearingen , Kevin Li , Marti Hearst, Faceted metadata for image search and browsing, Proceedings of the SIGCHI conference on Human factors in computing systems, April 05-10, 2003, Ft. Lauderdale, Florida, USA
[doi> 10.1145/642611.642681]
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18
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19
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20
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