Article

Managing syntactic variation in text retrieval

Authors:

Jesús Vilares,

Carlos Gómez-Rodríguez,

Miguel A. AlonsoAuthors Info & Claims

DocEng '05: Proceedings of the 2005 ACM symposium on Document engineering

Pages 162 - 164

https://doi.org/10.1145/1096601.1096643

Published: 02 November 2005 Publication History

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Abstract

Information Retrieval systems are limited by the linguistic variation of language. The use of Natural Language Processing techniques to manage this problem has been studied for a long time, but mainly focusing on English. In this paper we deal with European languages, taking Spanish as a case in point. Two different sources of syntactic information, queries and documents, are studied in order to increase the performance of Information Retrieval systems.

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Cited By

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Carrillo MLópez-López A(2008)Towards an Enhanced Vector Model to Encode Textual Relations: Experiments Retrieving InformationArtificial Intelligence in Theory and Practice II10.1007/978-0-387-09695-7_37(383-392)Online publication date: 2008
https://doi.org/10.1007/978-0-387-09695-7_37
Georg GJaulent MKing PSimske S(2007)A document engineering environment for clinical guidelinesProceedings of the 2007 ACM symposium on Document engineering10.1145/1284420.1284440(69-78)Online publication date: 28-Aug-2007
https://dl.acm.org/doi/10.1145/1284420.1284440

Index Terms

Managing syntactic variation in text retrieval
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Information retrieval

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A lemmatization method for Mongolian and its application to indexing for information retrieval

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Lexical and Syntactic knowledge for Information Retrieval

Traditional Information Retrieval (IR) models assume that the index terms of queries and documents are statistically independent of each other, which is intuitively wrong. This paper proposes the incorporation of the lexical and syntactic knowledge ...

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Published In

DocEng '05: Proceedings of the 2005 ACM symposium on Document engineering

November 2005

252 pages

ISBN:1595932402

DOI:10.1145/1096601

General Chair:
Anthony Wiley
Hewlett Packard Laboratories, UK
,
Program Chair:
Peter R. King
University of Manitoba, Canada

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

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Published: 02 November 2005

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November 2 - 4, 2005

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Carrillo MLópez-López A(2008)Towards an Enhanced Vector Model to Encode Textual Relations: Experiments Retrieving InformationArtificial Intelligence in Theory and Practice II10.1007/978-0-387-09695-7_37(383-392)Online publication date: 2008
https://doi.org/10.1007/978-0-387-09695-7_37
Georg GJaulent MKing PSimske S(2007)A document engineering environment for clinical guidelinesProceedings of the 2007 ACM symposium on Document engineering10.1145/1284420.1284440(69-78)Online publication date: 28-Aug-2007
https://dl.acm.org/doi/10.1145/1284420.1284440

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Extraction of complex index terms in non-English IR: A shallow parsing based approach

A lemmatization method for Mongolian and its application to indexing for information retrieval

Lexical and Syntactic knowledge for Information Retrieval

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