Advertisement

Ontology as a Search-Tool: A Study of Real Users’ Query Formulation With and Without Conceptual Support

  • Sari Suomela
  • Jaana Kekäläinen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3408)

Abstract

This study examines 16 real users’ use of an ontology as a search tool. The users’ queries constructed with the help of a Concept-based Information Retrieval Interface (CIRI) were compared to queries created independently based on the same search task description. Also the effectiveness of the CIRI queries was compared to the users’ unaided queries. The simulated search task method was used to make the searching situations as close to real as possible. Due to CIRI’s query expansion feature the number of search terms was remarkably higher in ontology queries than in Direct interface queries. The search results were evaluated with generalised precision and generalised relative recall as well as precision based on personal assessments. The Direct interface queries performed better in all methods of comparison.

Keywords

Search Task Test User Query Expansion Real User Query Formulation 
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.
    Airio, E., Järvelin, K., Suomela, S., Saatsi, P., Kekäläinen, J.: CIRI - An Ontology-based Query Interface for Text Retrieval. The Web Intelligence –symposium, Helsinki, Finland (2004), Available at, http://www.cs.helsinki.fi/group/seco/conference/step2004/material.html, [Cited October 26, 2004]
  2. 2.
    Allan, J., Callan, J., Croft, B., Ballesteros, L., Byrd, D., Swan, R., Xu, J.: INQUERY does battle with TREC-6 (1997), Available at, http://trec.nist.gov/pubs/trec6/papers/umass-trec97.ps, [Cited 26.10.2004]
  3. 3.
    Belkin, N.J., Cool, C., Kelly, D., Lin, S.J., Park, S.Y., Perez-Carballo, J., Sikora, C.: Iterative exploration, design and evaluation of support for query formulation in interactive information retrieval. Information Processing & Management 37, 403–434 (2001)zbMATHCrossRefGoogle Scholar
  4. 4.
    Borlund, P.: Evaluation of interactive information retrieval systems. Doctoral dissertation. Åbo Akademi University Press, Åbo (2000)Google Scholar
  5. 5.
    Efthimiadis, E.N.: Query expansion. In: Williams, M.E. (ed.) Annual Review of Information Science and Technology, Medford, NJ. Information Today, vol. 31, pp. 121–187 (1996)Google Scholar
  6. 6.
    Guarino, N.: Formal ontology, conceptual analysis and knowledge representation. International Journal of Human and Computer Studies 43, 625–640 (1995)CrossRefGoogle Scholar
  7. 7.
    Guarino, N., Masolo, C., Vetere, G.: OntoSeek: Using large linguistic ontologies for gathering information resources from the Web. LADSEB-CNR Technical Report 01/98 (1998)Google Scholar
  8. 8.
    ISO International Standard 2788. Documentation - Guidelines for the establishment and development of monolingual thesauri. International Organization for Standardization (1986) Google Scholar
  9. 9.
    Joho, H., Sanderson, M., Beaulieu, M.: A study of user interaction with a concept-based interactive query expansion support tool. In: McDonald, S., Tait, J.I. (eds.) ECIR 2004. LNCS, vol. 2997, pp. 42–56. Springer, Berlin (2004)CrossRefGoogle Scholar
  10. 10.
    Jones, S., Gatford, M., Robertson, S., Hancock-Beaulieu, M., Secker, J.: Interactive thesaurus navigation: Intelligence rules ok? Journal of the American Society for Information Science 46, 52–59 (1995)CrossRefGoogle Scholar
  11. 11.
    Järvelin, K., Kekäläinen, J., Niemi, T.: ExpansionTool: Concept-based query expansion and construction. Information Retrieval 4, 231–255 (2001)zbMATHCrossRefGoogle Scholar
  12. 12.
    Järvelin, K., Kristensen, J., Niemi, T., Sormunen, E., Keskustalo, H.: A deductive data model for query expansion. In: Frei, H.-P., Harman, D., Schäuble, P., Wilkinson, R. (eds.) Proceedings of the 19th Annual International ACM–SIGIR Conference on Research and Development in Information Retrieval, pp. 235–249. ACM press, New York (1996)CrossRefGoogle Scholar
  13. 13.
    Kekäläinen, J.: The effects of query complexity, expansion and structure on retrieval performance in probabilistic text retrieval. PhD dissertation, Department of Information Studies, University of Tampere. Acta Universitatis Tamperensis 678 (1999)Google Scholar
  14. 14.
    Kekäläinen, J., Järvelin, K.: Using graded relevance assessments in IR evaluation. Journal of the American Society for Information Science and Technology 53, 1120–1129 (2002)CrossRefGoogle Scholar
  15. 15.
    Over, P.: The TREC interactive track: an annotated bibliography. Information Processing & Management 37, 369–381 (2001)zbMATHCrossRefGoogle Scholar
  16. 16.
    Sihvonen, A., Vakkari, P.: Subject knowledge improves interactive query expansion assisted by a thesaurus. To appear in Journal of Documentation (2004)Google Scholar
  17. 17.
    Sparck Jones, K.: Automatic indexing. Journal of Documentation 30, 393–432 (1974)CrossRefGoogle Scholar
  18. 18.
    Sutcliffe, A.G., Ennis, M., Watkinson, S.J.: Empirical studies of end-user information searching. Journal of the American Society for Information Science 51, 1211–1231 (2000)CrossRefGoogle Scholar
  19. 19.
    Turtle, H.R.: Inference networks for document retrieval. Ph.D. dissertation. COINS Technical Report 90–92. Computer and information Science Department, University of Massachusetts (1990)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sari Suomela
    • 1
  • Jaana Kekäläinen
    • 1
  1. 1.Department of Information StudiesUniversity of TampereFinland

Personalised recommendations