research-article

Discovering key concepts in verbose queries

Authors:

Michael Bendersky,

W. Bruce CroftAuthors Info & Claims

SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval

Pages 491 - 498

https://doi.org/10.1145/1390334.1390419

Published: 20 July 2008 Publication History

Abstract

Current search engines do not, in general, perform well with longer, more verbose queries. One of the main issues in processing these queries is identifying the key concepts that will have the most impact on effectiveness. In this paper, we develop and evaluate a technique that uses query-dependent, corpus-dependent, and corpus-independent features for automatic extraction of key concepts from verbose queries. We show that our method achieves higher accuracy in the identification of key concepts than standard weighting methods such as inverse document frequency. Finally, we propose a probabilistic model for integrating the weighted key concepts identified by our method into a query, and demonstrate that this integration significantly improves retrieval effectiveness for a large set of natural language description queries derived from TREC topics on several newswire and web collections.

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Cited By

Gabory ELiu CLoukides GPissis SZuba W(2024)Space-Efficient Indexes for Uncertain Strings2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00367(4828-4842)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00367
Chikkamath RRastogi DMaan MEndres M(2024)Is your search query well-formed? A natural query understanding for patent prior art searchWorld Patent Information10.1016/j.wpi.2023.10225476(102254)Online publication date: Mar-2024
https://doi.org/10.1016/j.wpi.2023.102254
Ayad LLoukides GPissis S(2023)Text Indexing for Long Patterns: Anchors are All you NeedProceedings of the VLDB Endowment10.14778/3598581.359858616:9(2117-2131)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.14778/3598581.3598586
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Index Terms

Discovering key concepts in verbose queries
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

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cover image ACM Conferences

SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval

July 2008

934 pages

ISBN:9781605581644

DOI:10.1145/1390334

General Chairs:
Tat-Seng Chua
National University of Singapore
,
Mun-Kew Leong
National Library Board, Singapore
,
Program Chairs:
Syung Hyon Myaeng
Information and Communications University, Korea
,
Douglas W. Oard
University of Maryland, College Park, USA
,
Fabrizio Sebastiani
Consiglio Nazionale delle Ricerche, Italy

Copyright © 2008 ACM.

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Publication History

Published: 20 July 2008

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SIGIR '08: The 31st Annual International ACM SIGIR Conference

July 20 - 24, 2008

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Cited By

Gabory ELiu CLoukides GPissis SZuba W(2024)Space-Efficient Indexes for Uncertain Strings2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00367(4828-4842)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00367
Chikkamath RRastogi DMaan MEndres M(2024)Is your search query well-formed? A natural query understanding for patent prior art searchWorld Patent Information10.1016/j.wpi.2023.10225476(102254)Online publication date: Mar-2024
https://doi.org/10.1016/j.wpi.2023.102254
Ayad LLoukides GPissis S(2023)Text Indexing for Long Patterns: Anchors are All you NeedProceedings of the VLDB Endowment10.14778/3598581.359858616:9(2117-2131)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.14778/3598581.3598586
Zhou YHuang HWu Z(2023)Boosting legal case retrieval by query content selection with large language modelsProceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region10.1145/3624918.3625328(176-184)Online publication date: 26-Nov-2023
https://dl.acm.org/doi/10.1145/3624918.3625328
Samel KLi CKong WChen TZhang MGupta SKhadanga SXu WWang XKolipaka KBendersky MNajork MSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)End-to-End Query Term WeightingProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599815(4778-4786)Online publication date: 6-Aug-2023
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Ma ZDou ZXu WZhang XJiang HCao ZWen JDemartini GZuccon GCulpepper JHuang ZTong H(2021)Pre-training for Ad-hoc RetrievalProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482286(1212-1221)Online publication date: 26-Oct-2021
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Mishra SSaini NSaha SBhattacharyya P(2021)Scientific document summarization in multi-objective clustering frameworkApplied Intelligence10.1007/s10489-021-02376-5Online publication date: 23-May-2021
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Rasheed IBanka HKhan H(2021)Pseudo-relevance feedback based query expansion using boosting algorithmArtificial Intelligence Review10.1007/s10462-021-09972-4Online publication date: 20-Feb-2021
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Sar Shalom OResheff HZhicharevich ACohen R(2020)Distant Supervision for Keyphrase Extraction using Search Queries2020 IEEE Sixth International Conference on Big Data Computing Service and Applications (BigDataService)10.1109/BigDataService49289.2020.00019(70-77)Online publication date: Aug-2020
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