Article

An investigation of broad coverage automatic pronoun resolution for information retrieval

Authors:

Richard J. Edens,

Helen L. Gaylard,

Gareth J. F. Jones,

Adenike M. Lam-AdesinaAuthors Info & Claims

SIGIR '03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval

Pages 381 - 382

https://doi.org/10.1145/860435.860511

Published: 28 July 2003 Publication History

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Abstract

Term weighting methods have been shown to give significant increases in information retrieval performance. The presence of pronomial references in documents reduces the term frequencies of associated words with a consequent effect on term weights and information retrieval behaviour. This investigation explores the impact on information retrieval performance of broad coverage automatic pronoun resolution. Results indicate that this approach has potential to improve both precision at fixed cutoff levels and average precision.

References

[1]

B. J. Grosz, A. K. Joshi and S. Weinstein. Centering: A Framework for Modeling the Local Coherence of Discourse. Computational Linguistics, 21(2), pages 203--225, 1995.

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[2]

S. E. Robertson, et al. Okapi at TREC-3. In D. K. Harman, editor, Proceedings of TREC-3, pages 109--126. NIST, 1995.

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[3]

A. M. Lam-Adesina and G. J. F. Jones. Applying Summarization Techniques for Term Selection in Relevance Feedback. In ACM SIGIR 2001, pages 1--9, New Orleans, 2001.

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Cao YDaumé H(2021)Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning LifecycleComputational Linguistics10.1162/coli_a_0041347:3(615-661)Online publication date: 3-Nov-2021
https://doi.org/10.1162/coli_a_00413
Wu ZLv YFuxman ALi JWang XGarofalakis MSoboroff ISuel TWang M(2014)Searching Locally-Defined EntitiesProceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management10.1145/2661829.2661954(1499-1508)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2661829.2661954
Na SNg HAllan JAslam JSanderson MZhai CZobel J(2009)A 2-poisson model for probabilistic coreference of named entities for improved text retrievalProceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval10.1145/1571941.1571990(275-282)Online publication date: 19-Jul-2009
https://dl.acm.org/doi/10.1145/1571941.1571990

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An investigation of broad coverage automatic pronoun resolution for information retrieval
1. Information systems
  1. Information retrieval

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Published In

SIGIR '03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval

July 2003

490 pages

ISBN:1581136463

DOI:10.1145/860435

General Chairs:
Charles Clarke
University of Waterloo, Canada
,
Gordon Cormack
University of Waterloo, Canada
,
Program Chairs:
Jamie Callan
Carnegie Mellon University, Pittsburgh, PA
,
David Hawking
Australian National University, Australia
,
Alan Smeaton
Dublin City University, Ireland

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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Association for Computing Machinery

New York, NY, United States

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Published: 28 July 2003

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SIGIR03: The 26th ACM/SIGIR International Symposium on Information Retrieval

July 28 - August 1, 2003

Toronto, Canada

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SIGIR '03 Paper Acceptance Rate 46 of 266 submissions, 17%;

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

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Cited By

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Cao YDaumé H(2021)Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning LifecycleComputational Linguistics10.1162/coli_a_0041347:3(615-661)Online publication date: 3-Nov-2021
https://doi.org/10.1162/coli_a_00413
Wu ZLv YFuxman ALi JWang XGarofalakis MSoboroff ISuel TWang M(2014)Searching Locally-Defined EntitiesProceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management10.1145/2661829.2661954(1499-1508)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2661829.2661954
Na SNg HAllan JAslam JSanderson MZhai CZobel J(2009)A 2-poisson model for probabilistic coreference of named entities for improved text retrievalProceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval10.1145/1571941.1571990(275-282)Online publication date: 19-Jul-2009
https://dl.acm.org/doi/10.1145/1571941.1571990

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Term weighting for information retrieval based on term's discrimination power

Text Retrieval based on Least Information Measurement

Improving Information Retrieval Through a Global Term Weighting Scheme

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