Article

Query expansion using associated queries

Authors:

Bodo Billerbeck,

Hugh E. Williams,

Justin ZobelAuthors Info & Claims

CIKM '03: Proceedings of the twelfth international conference on Information and knowledge management

Pages 2 - 9

https://doi.org/10.1145/956863.956866

Published: 03 November 2003 Publication History

Abstract

Hundreds of millions of users each day use web search engines to meet their information needs. Advances in web search effectiveness are therefore perhaps the most significant public outcomes of IR research. Query expansion is one such method for improving the effectiveness of ranked retrieval by adding additional terms to a query. In previous approaches to query expansion, the additional terms are selected from highly ranked documents returned from an initial retrieval run. We propose a new method of obtaining expansion terms, based on selecting terms from past user queries that are associated with documents in the collection. Our scheme is effective for query expansion for web retrieval: our results show relative improvements over unexpanded full text retrieval of 26%--29%, and 18%--20% over an optimised, conventional expansion approach.

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Cited By

Chandra GDwivedi S(2024)Query Expansion Using Proposed Location-Based Algorithm for Hindi–English CLIR: Analyzing Three Test CollectionsInternational Journal of Pattern Recognition and Artificial Intelligence10.1142/S021800142459001838:05Online publication date: 11-May-2024
https://doi.org/10.1142/S0218001424590018
Dong CLi YGong HChen MLi JShen YYang M(2022)A Survey of Natural Language GenerationACM Computing Surveys10.1145/355472755:8(1-38)Online publication date: 23-Dec-2022
https://dl.acm.org/doi/10.1145/3554727
Tamine LGoeuriot L(2021)Semantic Information Retrieval on Medical TextsACM Computing Surveys10.1145/346247654:7(1-38)Online publication date: 17-Sep-2021
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Index Terms

Query expansion using associated queries
1. Information systems
  1. Information retrieval
    1. Evaluation of retrieval results
      1. Relevance assessment
    2. Information retrieval query processing

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cover image ACM Conferences

CIKM '03: Proceedings of the twelfth international conference on Information and knowledge management

November 2003

592 pages

ISBN:1581137230

DOI:10.1145/956863

General Chair:
Donald Kraft
Louisiana State University
,
Program Chairs:
Ophir Frieder
Illinois Institute of Technology
,
Joachim Hammer
University of Florida
,
Sajda Qureshi
University of Nebraska, Omaha
,
Len Seligman
The MITRE Corporation

Copyright © 2003 ACM.

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Published: 03 November 2003

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Cited By

Chandra GDwivedi S(2024)Query Expansion Using Proposed Location-Based Algorithm for Hindi–English CLIR: Analyzing Three Test CollectionsInternational Journal of Pattern Recognition and Artificial Intelligence10.1142/S021800142459001838:05Online publication date: 11-May-2024
https://doi.org/10.1142/S0218001424590018
Dong CLi YGong HChen MLi JShen YYang M(2022)A Survey of Natural Language GenerationACM Computing Surveys10.1145/355472755:8(1-38)Online publication date: 23-Dec-2022
https://dl.acm.org/doi/10.1145/3554727
Tamine LGoeuriot L(2021)Semantic Information Retrieval on Medical TextsACM Computing Surveys10.1145/346247654:7(1-38)Online publication date: 17-Sep-2021
https://dl.acm.org/doi/10.1145/3462476
Chandra GDwivedi S(2020)Term Ordering-Based Query Expansion Technique for Hindi-English CLIR SystemHandling Priority Inversion in Time-Constrained Distributed Databases10.4018/978-1-7998-2491-6.ch016(283-302)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-2491-6.ch016
Benham RMackenzie JMoffat ACulpepper J(2019)Boosting Search Performance Using Query VariationsACM Transactions on Information Systems10.1145/334500137:4(1-25)Online publication date: 4-Oct-2019
https://dl.acm.org/doi/10.1145/3345001
Zhang BQi XHan X(2019)An Advanced User Intent Model Based On User Learning ProcessInternational Journal of Pattern Recognition and Artificial Intelligence10.1142/S021800142050024X34:09(2050024)Online publication date: 13-Dec-2019
https://doi.org/10.1142/S021800142050024X
Chandra GDwivedi S(2019)Query Expansion for Effective Retrieval Results of Hindi–English Cross-Lingual IRApplied Artificial Intelligence10.1080/08839514.2019.157701833:7(567-593)Online publication date: 8-Apr-2019
https://doi.org/10.1080/08839514.2019.1577018
Sharma DPamula RChauhan D(2019)A hybrid evolutionary algorithm based automatic query expansion for enhancing document retrieval systemJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01247-915:1(829-848)Online publication date: 25-Feb-2019
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Kumar VSingh V(2018)What’s on Your Mind: Automatic Intent Modeling for Data ExplorationAdvances in Data and Information Sciences10.1007/978-981-13-0277-0_6(65-75)Online publication date: 29-Jun-2018
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Brusilovsky PSmyth BShapira B(2018)Social SearchSocial Information Access10.1007/978-3-319-90092-6_7(213-276)Online publication date: 3-May-2018
https://doi.org/10.1007/978-3-319-90092-6_7
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