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Selecting related terms in query-logs using two-stage SimRank

Published: 24 October 2011 Publication History

Abstract

It is commonly believed that query logs from Web search are a gold mine for search business, because they reflect users' preference over Web pages presented by search engines, so a lot of studies based on query logs have been carried out in the last few years. In this study, we assume that two queries are relevant to each other when they have same clicked page in their result lists, and we also consider the queries' topics of user's need. Thus, we propose a Two-Stage SimRank (called TSS in this paper) algorithm based on SimRank and some clustering algorithms to compute the similarity among queries, and then use it to discover relevant terms for query expansion, considering the information of topics and the global relationships of queries concurrently, with a query log collected by a practical search engine. Experimental results on two TREC test collections show that our approach can discover qualified terms effectively and improve retrieval performance.

References

[1]
Indri toolkit. http://www.lemurproject.org/indri.php.
[2]
Open directory project (odp). http://www.dmoz.org/.
[3]
I. Antonellis, H. G. Molina, and C. C. Chang. Simrank: Query rewriting through link analysis of the click graph. In Proceedings of VLDB 2008, pages 408--421, August 2008.
[4]
P. Boldi, F. Bonchi, and C. Castillo. Query suggestions using query-flow graphs. In Proceedings of WSCD 2009, pages 51--58. ACM, February 2009.
[5]
B. Croft, D. Metzler, and T. Strohman. Search Engines: Information Retrieval in Practice. Addison-Wesley Publishing Company, Reading, Massachusetts, 2009.
[6]
G. Jeh and J. Widom. Simrank: A measure of structural-context similarity. In Proceedings of SIGKDD 2002, pages 538--543. ACM, July 2002.
[7]
V. Lavrenko and W. B. Croft. Relevance-based language models. In SIGIR 2001: Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, pages 120--127. ACM, September 2001.
[8]
K. S. Lee, W. B. Croft, and J. Allan. A cluster-based resampling method for pseudo-relevance feedback. In SIGIR 2008: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, pages 235--242. ACM, July 2008.
[9]
Y. L. Ma, H. F. Lin, and S. Jin. A revised simrank approach for query expansion. In Proceedings of AIRS 2010, pages 564--575. Springer, December 2010.
[10]
T. Tao and C. X. Zhai. Regularized estimation of mixture models for robust pseudo-relevance feedback. In SIGIR 2006: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, pages 162--169. ACM, August 2006.

Cited By

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  • (2015)Selecting expansion terms based on path-constrained term-relationship graphs2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)10.1109/FSKD.2015.7382159(1460-1464)Online publication date: Aug-2015
  • (2015)Query recommendation based on irrelevant feedback analysis2015 8th International Conference on Biomedical Engineering and Informatics (BMEI)10.1109/BMEI.2015.7401583(644-648)Online publication date: Oct-2015
  • (2014)Query recommendation in the information domain of childrenJournal of the Association for Information Science and Technology10.1002/asi.2305565:7(1368-1384)Online publication date: 1-Jul-2014
  • Show More Cited By

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cover image ACM Conferences
CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management
October 2011
2712 pages
ISBN:9781450307178
DOI:10.1145/2063576
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

Publication History

Published: 24 October 2011

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Author Tags

  1. query expansion
  2. query logs.
  3. search engine

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Cited By

View all
  • (2015)Selecting expansion terms based on path-constrained term-relationship graphs2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)10.1109/FSKD.2015.7382159(1460-1464)Online publication date: Aug-2015
  • (2015)Query recommendation based on irrelevant feedback analysis2015 8th International Conference on Biomedical Engineering and Informatics (BMEI)10.1109/BMEI.2015.7401583(644-648)Online publication date: Oct-2015
  • (2014)Query recommendation in the information domain of childrenJournal of the Association for Information Science and Technology10.1002/asi.2305565:7(1368-1384)Online publication date: 1-Jul-2014
  • (2012)Query recommendation for childrenProceedings of the 21st ACM international conference on Information and knowledge management10.1145/2396761.2398562(2010-2014)Online publication date: 29-Oct-2012

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