research-article

Generating reformulation trees for complex queries

Authors:

W. Bruce CroftAuthors Info & Claims

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

Pages 525 - 534

https://doi.org/10.1145/2348283.2348355

Published: 12 August 2012 Publication History

Abstract

Search queries have evolved beyond keyword queries. Many complex queries such as verbose queries, natural language question queries and document-based queries are widely used in a variety of applications. Processing these complex queries usually requires a series of query operations, which results in multiple sequences of reformulated queries. However, previous query representations, either the "bag of words" method or the recently proposed "query distribution" method, cannot effectively model these query sequences, since they ignore the relationships between two queries. In this paper, a reformulation tree framework is proposed to organize multiple sequences of reformulated queries as a tree structure, where each path of the tree corresponds to a sequence of reformulated queries. Specifically, a two-level reformulation tree is implemented for verbose queries. This tree effectively combines two query operations, i.e., subset selection and query substitution, within the same framework. Furthermore, a weight estimation approach is proposed to assign weights to each node of the reformulation tree by considering the relationships with other nodes and directly optimizing retrieval performance. Experiments on TREC collections show that this reformulation tree based representation significantly outperforms the state-of-the-art techniques.

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Cited By

Yan WWang YHuang CWu S(2020)Word Embedding-Based Reformulation for Long Queries in Information SearchWeb Information Systems and Applications10.1007/978-3-030-60029-7_19(202-214)Online publication date: 23-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-60029-7_19
Chaa MNouali OBellot PSheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)New technique to deal with verbose queries in social book searchProceedings of the International Conference on Web Intelligence10.1145/3106426.3106481(799-806)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3106481
Gupta MBendersky MBaeza-Yates RLalmas MMoffat ARibeiro-Neto B(2015)Information Retrieval with Verbose QueriesProceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/2766462.2767877(1121-1124)Online publication date: 9-Aug-2015
https://dl.acm.org/doi/10.1145/2766462.2767877
Show More Cited By

Index Terms

Generating reformulation trees for complex queries
1. Information systems
  1. Information retrieval

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cover image ACM Conferences

SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval

August 2012

1236 pages

ISBN:9781450314725

DOI:10.1145/2348283

General Chair:
William Hersh
Oregon Health & Science University, USA
,
Program Chairs:
Jamie Callan
Carnegie Mellon University, USA
,
Yoelle Maarek
Yahoo! Research, Israel
,
Mark Sanderson
Royal Melbourne Institute of Technology, Australia

Copyright © 2012 ACM.

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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SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 August 2012

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SIGIR '12

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SIGIR

SIGIR '12: The 35th International ACM SIGIR conference on research and development in Information Retrieval

August 12 - 16, 2012

Oregon, Portland, USA

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

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Cited By

Yan WWang YHuang CWu S(2020)Word Embedding-Based Reformulation for Long Queries in Information SearchWeb Information Systems and Applications10.1007/978-3-030-60029-7_19(202-214)Online publication date: 23-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-60029-7_19
Chaa MNouali OBellot PSheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)New technique to deal with verbose queries in social book searchProceedings of the International Conference on Web Intelligence10.1145/3106426.3106481(799-806)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3106481
Gupta MBendersky MBaeza-Yates RLalmas MMoffat ARibeiro-Neto B(2015)Information Retrieval with Verbose QueriesProceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/2766462.2767877(1121-1124)Online publication date: 9-Aug-2015
https://dl.acm.org/doi/10.1145/2766462.2767877
Wang YLiu JChen JHuang Y(2014)Finding similar queries based on query representation analysisWorld Wide Web10.1007/s11280-013-0233-517:5(1161-1188)Online publication date: 1-Sep-2014
https://dl.acm.org/doi/10.1007/s11280-013-0233-5
Dietz LWang ZHuston SCroft WHe QIyengar ANejdl WPei JRastogi R(2013)Retrieving opinions from discussion forumsProceedings of the 22nd ACM international conference on Information & Knowledge Management10.1145/2505515.2507861(1225-1228)Online publication date: 27-Oct-2013
https://dl.acm.org/doi/10.1145/2505515.2507861

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