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Article

Exploiting redundancy in question answering

Authors:

Charles L. A. Clarke,

Gordon V. Cormack,

Thomas R. LynamAuthors Info & Claims

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

Pages 358 - 365

https://doi.org/10.1145/383952.384024

Published: 01 September 2001 Publication History

Abstract

Our goal is to automatically answer brief factual questions of the form ``When was the Battle of Hastings?'' or ``Who wrote The Wind in the Willows?''. Since the answer to nearly any such question can now be found somewhere on the Web, the problem reduces to finding potential answers in large volumes of data and validating their accuracy. We apply a method for arbitrary passage retrieval to the first half of the problem and demonstrate that answer redundancy can be used to address the second half. The success of our approach depends on the idea that the volume of available Web data is large enough to supply the answer to most factual questions multiple times and in multiple contexts. A query is generated from a question and this query is used to select short passages that may contain the answer from a large collection of Web data. These passages are analyzed to identify candidate answers. The frequency of these candidates within the passages is used to ``vote'' for the most likely answer. The approach is experimentally tested on questions taken from the TREC-9 question-answering test collection. As an additional demonstration, the approach is extended to answer multiple choice trivia questions of the form typically asked in trivia quizzes and television game shows.

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Cited By

Kamalloo EClarke CRafiei DChen HDuh WHuang HKato MMothe JPoblete B(2023)Limitations of Open-Domain Question Answering Benchmarks for Document-level ReasoningProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3592011(2123-2128)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3592011
Yadegari MKamalloo ERafiei DAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)Detecting Frozen Phrases in Open-Domain Question AnsweringProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531793(1990-1996)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531793
Su LZhang RGuo JFan YChen JLan YCheng XLewin-Eytan LCarmel DYom-Tov EAgichtein EGabrilovich E(2021)Beyond Relevance: Trustworthy Answer Selection via Consensus VerificationProceedings of the 14th ACM International Conference on Web Search and Data Mining10.1145/3437963.3441781(562-570)Online publication date: 8-Mar-2021
https://dl.acm.org/doi/10.1145/3437963.3441781
Show More Cited By

Index Terms

Exploiting redundancy in question answering
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Information retrieval

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Published In

cover image ACM Conferences

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)

Copyright © 2001 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: 01 September 2001

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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

Kamalloo EClarke CRafiei DChen HDuh WHuang HKato MMothe JPoblete B(2023)Limitations of Open-Domain Question Answering Benchmarks for Document-level ReasoningProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3592011(2123-2128)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3592011
Yadegari MKamalloo ERafiei DAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)Detecting Frozen Phrases in Open-Domain Question AnsweringProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531793(1990-1996)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531793
Su LZhang RGuo JFan YChen JLan YCheng XLewin-Eytan LCarmel DYom-Tov EAgichtein EGabrilovich E(2021)Beyond Relevance: Trustworthy Answer Selection via Consensus VerificationProceedings of the 14th ACM International Conference on Web Search and Data Mining10.1145/3437963.3441781(562-570)Online publication date: 8-Mar-2021
https://dl.acm.org/doi/10.1145/3437963.3441781
Garg ABadal TMukhopadhyay D(2021)QA System: Business Intelligence in HealthcareAdvanced Computing10.1007/978-981-16-0401-0_16(212-223)Online publication date: 11-Feb-2021
https://doi.org/10.1007/978-981-16-0401-0_16
Clarke C(2018)Web Question AnsweringEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_1363(4637-4643)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_1363
Zhang HRao JLin JSmucker MKando NSakai TJoho HLi Hde Vries AWhite R(2017)Automatically Extracting High-Quality Negative Examples for Answer Selection in Question AnsweringProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3077136.3080645(797-800)Online publication date: 7-Aug-2017
https://dl.acm.org/doi/10.1145/3077136.3080645
Bachrach YZukov-Gregoric ACoope STovell EMaksak BRodriguez JMcMurtie CBordbar M(2017)An Attention Mechanism for Neural Answer Selection Using a Combined Global and Local View2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI)10.1109/ICTAI.2017.00072(425-432)Online publication date: Nov-2017
https://doi.org/10.1109/ICTAI.2017.00072
Wang XLi ZTang J(2017)Multimedia news QAImage and Vision Computing10.1016/j.imavis.2017.01.00460:C(162-170)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1016/j.imavis.2017.01.004
Amarger FChanet JHaemmerlé OHernandez NRoussey C(2016)Knowledge Engineering Method Based on Consensual Knowledge and Trust Computation: The MUSCKA SystemGraph-Based Representation and Reasoning10.1007/978-3-319-40985-6_14(177-190)Online publication date: 10-Jun-2016
https://doi.org/10.1007/978-3-319-40985-6_14
Clarke C(2016)Web Question AnsweringEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_1363-2(1-7)Online publication date: 28-Dec-2016
https://doi.org/10.1007/978-1-4899-7993-3_1363-2
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