Article

Query clustering using content words and user feedback

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SIGIR '01: Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 442 - 443

https://doi.org/10.1145/383952.384083

Published: 01 September 2001 Publication History

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Abstract

Query clustering is crucial for automatically discovering frequently asked queries (FAQs) or most popular topics on a question-answering search engine. Due to the short length of queries, the traditional approaches based on keywords are not suitable for query clustering. This paper describes our attempt to cluster similar queries according to their contents as well as the document click information in the user logs.

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Cited By

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Qin JXiao CHu SZhang JWang WIshikawa YTsuda KSadakane K(2019)Efficient query autocompletion with edit distance-based error toleranceThe VLDB Journal10.1007/s00778-019-00595-429:4(919-943)Online publication date: 14-Dec-2019
https://doi.org/10.1007/s00778-019-00595-4
Jiang DLeung KNg W(2016)Query intent mining with multiple dimensions of web search dataWorld Wide Web10.1007/s11280-015-0336-219:3(475-497)Online publication date: 1-May-2016
https://dl.acm.org/doi/10.1007/s11280-015-0336-2
Fan FQiang RLv CYang JBailey JMoffat AAggarwal Cde Rijke MKumar RMurdock VSellis TYu J(2015)Improving Microblog Retrieval with Feedback Entity ModelProceedings of the 24th ACM International on Conference on Information and Knowledge Management10.1145/2806416.2806461(573-582)Online publication date: 17-Oct-2015
https://dl.acm.org/doi/10.1145/2806416.2806461
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Query clustering using content words and user feedback

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Published In

SIGIR '01: Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval

September 2001

454 pages

ISBN:1581133316

DOI:10.1145/383952

Chairmen:
Donald H. Kraft
Louisiana State Univ.
,
W. Bruce Croft
University of Massachusetts, (For the Americas)
,
David J. Harper
The Robert Gordon University, (For Europe and Africa)
,
Justin Zobel
RMIT University, (For Asia and Australasia)

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 01 September 2001

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SIGIR01

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SIGIR

SIGIR01: 24th ACM/SIGIR International Conference on Research and Development in Information Retrieval

Louisiana, New Orleans, USA

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SIGIR '01 Paper Acceptance Rate 47 of 201 submissions, 23%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

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Qin JXiao CHu SZhang JWang WIshikawa YTsuda KSadakane K(2019)Efficient query autocompletion with edit distance-based error toleranceThe VLDB Journal10.1007/s00778-019-00595-429:4(919-943)Online publication date: 14-Dec-2019
https://doi.org/10.1007/s00778-019-00595-4
Jiang DLeung KNg W(2016)Query intent mining with multiple dimensions of web search dataWorld Wide Web10.1007/s11280-015-0336-219:3(475-497)Online publication date: 1-May-2016
https://dl.acm.org/doi/10.1007/s11280-015-0336-2
Fan FQiang RLv CYang JBailey JMoffat AAggarwal Cde Rijke MKumar RMurdock VSellis TYu J(2015)Improving Microblog Retrieval with Feedback Entity ModelProceedings of the 24th ACM International on Conference on Information and Knowledge Management10.1145/2806416.2806461(573-582)Online publication date: 17-Oct-2015
https://dl.acm.org/doi/10.1145/2806416.2806461
Ghansah BWu SGhansah N(2015)Rankboost-Based Result Merging2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing10.1109/CIT/IUCC/DASC/PICOM.2015.136(907-914)Online publication date: Oct-2015
https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.136
Sharma SGupta P(2014)A Review on Methods for Query PersonalizationIntelligent Computing, Networking, and Informatics10.1007/978-81-322-1665-0_112(1099-1106)Online publication date: 2014
https://doi.org/10.1007/978-81-322-1665-0_112
(2013)Information MiningTextual Information Access10.1002/9781118562796.ch8(305-336)Online publication date: 14-Feb-2013
https://doi.org/10.1002/9781118562796.ch8
Mao YShen HSun C(2011)A probabilistic topic model with social tags for query reformulation in informational searchProceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I10.1007/978-3-642-25853-4_9(109-123)Online publication date: 17-Dec-2011
https://dl.acm.org/doi/10.1007/978-3-642-25853-4_9
Liu YZhang LSong RNie JWen JCheung DSong IChu WHu XLin J(2009)Clustering queries for better document rankingProceedings of the 18th ACM conference on Information and knowledge management10.1145/1645953.1646174(1569-1572)Online publication date: 2-Nov-2009
https://dl.acm.org/doi/10.1145/1645953.1646174
Arguello JCallan JDiaz FCheung DSong IChu WHu XLin J(2009)Classification-based resource selectionProceedings of the 18th ACM conference on Information and knowledge management10.1145/1645953.1646115(1277-1286)Online publication date: 2-Nov-2009
https://dl.acm.org/doi/10.1145/1645953.1646115
Ngok PZhiguo Gong (2009)Log mining to support web query expansions2009 International Conference on Information and Automation10.1109/ICINFA.2009.5204952(375-379)Online publication date: Jun-2009
https://doi.org/10.1109/ICINFA.2009.5204952
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