Article

Structured retrieval for question answering

Authors:

Matthew W. Bilotti,

Eric NybergAuthors Info & Claims

SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 351 - 358

https://doi.org/10.1145/1277741.1277802

Published: 23 July 2007 Publication History

Abstract

Bag-of-words retrieval is popular among Question Answering (QA) system developers, but it does not support constraint checking and ranking on the linguistic and semantic information of interest to the QA system. We present anapproach to retrieval for QA, applying structured retrieval techniques to the types of text annotations that QA systems use. We demonstrate that the structured approach can retrieve more relevant results, more highly ranked, compared with bag-of-words, on a sentence retrieval task. We also characterize the extent to which structured retrieval effectiveness depends on the quality of the annotations.

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Index Terms

Structured retrieval for question answering
1. Information systems
  1. Information retrieval
    1. Document representation

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Published In

cover image ACM Conferences

SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

July 2007

946 pages

ISBN:9781595935977

DOI:10.1145/1277741

General Chairs:
Wessel Kraaij
TNO, The Netherlands
,
Arjen P. de Vries
CWI, The Netherlands
,
Program Chairs:
Charles L. A. Clarke
University of Waterloo, Canada
,
Norbert Fuhr
University of Duisburg-Essen, Germany
,
Noriko Kando
National Institute of Informatics, Japan

Copyright © 2007 ACM.

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Publication History

Published: 23 July 2007

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SIGIR07

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SIGIR07: The 30th Annual International SIGIR Conference

July 23 - 27, 2007

Amsterdam, The Netherlands

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

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https://doi.org/10.1109/ICTACS62700.2024.10841223
Fan AWang SWang Y(2024)Legal Document Similarity Matching Based on Ensemble LearningIEEE Access10.1109/ACCESS.2024.337126212(33910-33922)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3371262
Cui MLi XQin P(2024)Explainable Knowledge-Based Learning for Online Medical Question AnsweringKnowledge Science, Engineering and Management10.1007/978-981-97-5489-2_26(294-304)Online publication date: 27-Jul-2024
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