Advertisement

SIGIR ’94 pp 61-69 | Cite as

Query Expansion using Lexical-Semantic Relations

  • Ellen M. Voorhees

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 WordNet. 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.

Keywords

Query Expansion Link Type Original Query Expansion Strategy Query Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    David C. Blair and M. E. Maron. Full-text information retrieval: Further analysis and clarification. Information Processing and Management, 26 (3): 437–447, 1990.CrossRefGoogle Scholar
  2. 2.
    A. F. Smeaton and C. J. van Rijsbergen. The retrieval effects of query expansion on a feedback document retrieval system. Computer Journal, 26: 239–246, 1983.CrossRefGoogle Scholar
  3. 3.
    C. T. Yu, C. Buckley, and G. Salton. A generalized term dependency model in information retrieval. Information Technology: Research and Development, 2: 129–154, 1983.Google Scholar
  4. 4.
    Helen J. Peat and Peter Willett. The limitations of term co-occurrence data for query expansion in document retrieval systems. Journal of the American Society for Information Science, 42 (5): 378–383, 1991.CrossRefGoogle Scholar
  5. 5.
    Scott Deerwester, Susan T. Dumais, George W. Fumas, Thomas K. Landauer, and Richard Harshman. Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41 (6): 391–407, 1990.CrossRefGoogle Scholar
  6. 6.
    G. Salton and M. E. Lesk. Computer evaluation of indexing and text processing. In Gerard Salton, editor, The SMART Retrieval System: Experiments in Automatic Document Processing, pages 143–180. Prentice-Hall, Inc. Englewood Cliffs, New Jersey, 1971.Google Scholar
  7. 7.
    Yih-Chen Wang, James Vandendorpe, and Martha Evens. Relational thesauri in information retrieval. Journal of the American. Society for Information Science, 36 (1): 15–27, January 1985.Google Scholar
  8. 8.
    George Miller. Special Issue, WordNet: An on-line lexical database. International Journal of Lexicography, 3(4), 1990.Google Scholar
  9. 9.
    Donna K. Harman. The first Text REtrieval Conference (TREC-1), Rockville, MD, U.S.A, 4–6 November, 1992. Information Processing and Management, 29 (4): 411–414, 1993.CrossRefGoogle Scholar
  10. 10.
    Chris Buckley. Implementation of the SMART information retrieval system. Technical Report 85686, Computer Science Department, Cornell University, Ithaca, New York, May 1985.Google Scholar
  11. 11.
    Edward A. Fox. Extending the Boolean and Vector Space Models of Information Retrieval with P-norm Queries and Multiple Concept Types. PhD thesis, Cornell University, 1983. University Microfilms, Ann Arbor, MI.Google Scholar
  12. 12.
    Chris Buckley, Gerard Salton, and James Allan. Automatic retrieval with locality information using SMART. In D. K. Harman, editor, Proceedings of the First Text REtrieval Conference (TREC-1), pages 59–72. NIST Special Publication 500–207, March 1993.Google Scholar
  13. 13.
    Ellen M. Voorhees. On expanding query vectors with lexically related words. In D. K. Harman, editor, Proceedings of the Second Text REtrieval Conference (TREC-2), 1993. In press.Google Scholar
  14. 14.
    Ellen M. Voorhees and Yuan-Wang Hou. Vector expansion in a large collection. In D. K. Harman, editor, Proceedings of the First Text REtrieval Conference (TREC-1), pages 343–351. NIST Special Publication 500–207, March 1993.Google Scholar
  15. 15.
    Karen Sparck Jones. A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation, 28 (1): 11–21, March 1972.CrossRefGoogle Scholar
  16. 16.
    Chris Buckley, James Allan, and Gerard Salton. Automatic routing and ad-hoc retrieval using SMART: TREC 2. In D. K. Harman, editor, Proceedings of the Second Text REtrieval Conference (TREC-2), 1993.Google Scholar

Copyright information

© Springer-Verlag London Limited 1994

Authors and Affiliations

  • Ellen M. Voorhees
    • 1
  1. 1.Siemens Corporate Research, Inc.PrincetonUSA

Personalised recommendations