Query Expansion Using Lexical-Semantic Relations.

Ellen M. Voorhees: Query Expansion Using Lexical-Semantic Relations. SIGIR 1994: 61-69

@inproceedings{DBLP:conf/sigir/Voorhees94,
  author    = {Ellen M. Voorhees},
  editor    = {W. Bruce Croft and
               C. J. van Rijsbergen},
  title     = {Query Expansion Using Lexical-Semantic Relations},
  booktitle = {Proceedings of the 17th Annual International ACM-SIGIR Conference
               on Research and Development in Information Retrieval. Dublin,
               Ireland, 3-6 July 1994 (Special Issue of the SIGIR Forum)},
  publisher = {ACM/Springer},
  year      = {1994},
  isbn      = {3-540-19889-X},
  pages     = {61-69},
  ee        = {db/conf/sigir/Voorhees94.html},
  crossref  = {DBLP:conf/sigir/94},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

BibTeX

Abstract

Applications such as office automation, news filtering, help facilities in complex systems, and the like require the ability to retrieve documents from full-text databases where vocabulary problems can be particularly severe. Experiments performed on small collections with single-domain thesauri suggest that expanding query vectors with words that are lexically related to the original query words can ameliorate some of the problems of mismatched vocabularies. This paper examines the utility of lexical query expansion in the large, diverse TREC collection. Concepts are represented by WordNet synonym sets and are expanded by following the typed links included in Word Net. Experimental results show this query expansion technique makes little difference in retrieval effectiveness if the original queries are relatively complete descriptions of the information being sought even when the concepts to be expanded are selected by hand. Less well developed queries can be significantly improved by expansion of hand-chosen concepts. However, an automatic procedure that can approximate the set of hand picked synonym sets has yet to be devised, and expanding by the synonym sets that are automatically generated can degrade retrieval performance.

Copyright © 1994 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.

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BibTeX

Printed Edition

W. Bruce Croft, C. J. van Rijsbergen (Eds.): Proceedings of the 17th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval. Dublin, Ireland, 3-6 July 1994 (Special Issue of the SIGIR Forum). ACM/Springer 1994, ISBN 3-540-19889-X
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Referenced by

Mathias Géry, M. Hatem Haddad: Knowledge Discovery for Automatic Query Expansion on the World-Wide Web. ER (Workshops) 1999: 334-347

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