Skip to main content
Springer Nature Link
Log in

Query Expansion Using Web Access Log Files

  • Conference paper
Database and Expert Systems Applications (DEXA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3588))

Included in the following conference series:

Abstract

Query Expansion has long been recognized as one of the effective methods in solving short queries and improving ranking accuracy in traditional IR research. Many variations of this method have been introduced throughout the past decades; however, few of them have incorporated web log information into the query expansion process. In this paper, we propose an expansion technique that expands document content at the initial index stage using queries extracted from the web log files. Our experimental results show that even with a minimal amount of real world log information available and a professionally cataloged knowledge structure to aid the search, there is still a significant improvement in using our query expansion method compared to the conventional query expansion ones.

This work was partially supported by the National Library of Medicine, Grant No. 1 G08 LM007877-01 and 1 G08 LM008054-01.

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

Access this chapter

Log in via an institution

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. Agrawal, R., Imielinski, T., Swami, A.: Mining Association Rules Between Sets of Items in Large Databases. In: ACM SIGMOD, pp. 1–10 (1993)

    Google Scholar 

  2. Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval, ch.  3. Addison Wesley/ACM Press, NY (1999)

    Google Scholar 

  3. Billerbeck, B., Scholer, F., Williams, H.E., Zobel, J.: Query Expansion using Associated Queries. In: CIKM, pp. 2–9 (2003)

    Google Scholar 

  4. Brajnik, G., Mizzaro, S., Tasso, C.: Evaluating User Interfaces to Information Retrieval Systems: A Case Study on User Support. In: ACM SIGIR, pp. 128–136 (1996)

    Google Scholar 

  5. Carpineto, C., Mori, R.D., Romano, G., Bigi, B.: An Information-Theoretic Approach to Automatic Query Expansion. ACM Transaction on Information Systems 19(1), 1–27 (2001)

    Article  Google Scholar 

  6. Carpineto, C., Romano, G.: Effective Reformulation of Boolean Queries with Concept Lattices. In: Andreasen, T., Christiansen, H., Larsen, H.L. (eds.) FQAS 1998. LNCS (LNAI), vol. 1495, pp. 83–94. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  7. Cooper, J.W., Byrd, R.J.: Lexical Navigation: Visually Prompted Query Expansion and Refinement. In: Proceedings of the 2nd ACM International Conference on digital Libraries, pp. 237–246 (1997)

    Google Scholar 

  8. Cui, H., Wen, J.R., Nie, J.Y., Ma, W.Y.: Probablistic query expansion using query logs. In: The Eleventh International World Wide Web Conference, pp. 325–332. ACM, New York (2002)

    Chapter  Google Scholar 

  9. Grefenstette, G.: Explorations in Automatic Thesaurus Discover. Kluwer Academic Publisher, MA (1994)

    Google Scholar 

  10. HEAL: http://www.healcentral.org (accessed on June 7th, 2005)

  11. Jensen, B.J., Sprink, A., Scaracevic, T.: Real life, real users and real needs: A study and analysis of users’ queries on the Web. Information Processing and Management 36(2), 207–277 (2000)

    Article  Google Scholar 

  12. MeSH: http://www.nlm.nih.gov/mesh/meshhome.html (accessed on June 7, 2005)

  13. Robertson, S.E., Walker, S.: Okapi/Keenbow at TREC-8. TREC-8, 151–162 (1999)

    Google Scholar 

  14. Salton, G.: The SMART retrieval system, ch.  14. Prentice-Hall, Englewood Cliffs (1971)

    Google Scholar 

  15. Sparck Jones, K.: Experiments in relevance weighting of search terms. Information Processing and Management 15, 133–144 (1979)

    Article  Google Scholar 

  16. Sparck Jones, K.: Search term relevance weighing given little relevance information. Information Processing and Management 35, 30–48 (1979)

    Google Scholar 

  17. Sparck Jones, K., Walker, S., Robertson, S.E.: A Probabilistic Model of Information Retrieval: Development and Comparative Experiments Part 1. Information Processing and Management 36, 779–808 (2000)

    Article  Google Scholar 

  18. Sparck Jones, K., Walker, S., Robertson, S.E.: A Probabilistic Model of Information Retrieval: Development and Comparative Experiments Part 2. Information Processing and Management 36, 809–840 (2000)

    Article  Google Scholar 

  19. Srivastava, J., Cooley, R., Deshpande, M., Tan, P.N.: Web Usage Mining, Discovery and Applications of Usage Patterns from the Web Data. SIGKDD Explorations 1(2), 12–23 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The University of Oklahoma, 200 Falgar Street, Norman, OK, 73019, USA

    Yun Zhu & Le Gruenwald

Authors
  1. Yun Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Le Gruenwald
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Copenhagen Business School, Centre for Applied ICT, 60 Howitzvej, 2000, Frederiksberg, DK

    Kim Viborg Andersen

  2. University Of Technology Sydney, NSW 2007, Australia

    John Debenham

  3. University of Linz, Altenbergerstraße 69, 4040, Linz, Austria

    Roland Wagner

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhu, Y., Gruenwald, L. (2005). Query Expansion Using Web Access Log Files. In: Andersen, K.V., Debenham, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2005. Lecture Notes in Computer Science, vol 3588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546924_67

Download citation

  • DOI: https://doi.org/10.1007/11546924_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28566-3

  • Online ISBN: 978-3-540-31729-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics