Skip to main content

Lazy Query Enrichment: A Method for Indexing Large Specialized Document Bases with Morphology and Concept Hierarchy

  • Conference paper
  • First Online:
Database and Expert Systems Applications (DEXA 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1873))

Included in the following conference series:

  • 1793 Accesses

Abstract

A full-text information retrieval system has to deal with various phenomena of string equivalence: ignore case matching, morphological inflection, derivation, synonymy, and hyponymy or hyperonymy. Technically, this can be handled either at the time of indexing by reducing equivalent strings to a common form or at the time of query processing by enriching the query with the whole set of the equivalent forms. We argue for that the latter way allows for greater flexibility and easier maintenance, while being more affordable than it is usually considered. Our proposal consists in enriching the query only with those forms that really appear in the document base. Our experiments with a thesaurus-based information retrieval system showed only insignificant increase of the query size on average with a 200-megabyte document base, even with highly inflective Spanish language.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Aho, Alfred V. Algorithms for finding patterns in strings. In J. van Leeuwen (ed.), Handbook of Theoretical Computer Science, chapter 5, pp. 254–300. Elsevier Science Publishers B. V., 1990.

    Google Scholar 

  2. Cassidy P. An Investigation of the Semantic Relations in the Roget’s Thesaurus: Preliminary Results. In: A. Gelbukh (ed.), Computational Linguistics and Intelligent Text Processing, IPN-UNAM, Mexico, to appear. See also Proc. of CICLing-2000, February 2000, CIC-IPN, Mexico City, ISBN 970-18-4206-5.

    Google Scholar 

  3. Gelbukh, A. A data structure for prefix search under access locality requirements and its application to spelling correction. Proc. of MICAI-2000: Mexican International Conference on Artificial Intelligence, Acapulco, Mexico, 2000.

    Google Scholar 

  4. Gelbukh, A., G. Sidorov, and A. Guzm’an-Arenas. Use of a Weighted Topic Hierarchy for Document Classification, Matousek et al., TSD-99: Text, Speech, Dialogue. Lecture Notes in Artificial Intelligence N 1692, Springer, 1999.

    Google Scholar 

  5. Gusfield, Dan. Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology. Cambridge University Press, 1997; ISBN: 0521585198.

    Google Scholar 

  6. Guzm’an-Arenas, Adolfo. Finding the main themes in a Spanish document, Journal Expert Systems with Applications, Vol. 14, No. 1/2. Jan/Feb 1998, pp. 139–148.

    Article  Google Scholar 

  7. Fellbaum, Ch. (ed.) WordNet as Electronic Lexical Database. MIT Press, 1998.

    Google Scholar 

  8. Frakes, W., and R. Baeza-Yates, editors. Information Retrieval: Data Structures and Algorithms. Prentice-Hall, 1992.

    Google Scholar 

  9. Hausser, Ronald. Three principled methods of automatic word form recognition. Proc. of VEXTAL: Venecia per il Tratamento Automatico delle Lingue. Venice, Italy, Sept. 1999.

    Google Scholar 

  10. Koskenniemi, Kimmo. Two-level Morphology: A General Computational Model for Word-Form Recognition and Production. University of Helsinki Publications, N 1l, 1983.

    Google Scholar 

  11. Kowalski, Gerald. Information Retrieval Systems Theory and Implementation, Kluwer Academic Publishers, 1997.

    Google Scholar 

  12. Lenat, D. B. and R. V. Guha. Building Large Knowledge Based Systems. Reading, Massachusetts: Addison Wesley, 1990. See also more recent publications on CYC project, http://www.cyc.com.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gelbukh, A.F. (2000). Lazy Query Enrichment: A Method for Indexing Large Specialized Document Bases with Morphology and Concept Hierarchy. In: Ibrahim, M., Küng, J., Revell, N. (eds) Database and Expert Systems Applications. DEXA 2000. Lecture Notes in Computer Science, vol 1873. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44469-6_49

Download citation

  • DOI: https://doi.org/10.1007/3-540-44469-6_49

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67978-3

  • Online ISBN: 978-3-540-44469-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics