Skip to main content

An Approach to Integrating Query Refinement in SQL

  • Conference paper
  • First Online:
Book cover Advances in Database Technology — EDBT 2002 (EDBT 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2287))

Included in the following conference series:

Abstract

With the emergence of applications that require contentbased similarity retrieval, techniques to support such a retrieval paradigm over database systems have emerged as a critical area of research. User subjectivity is an important aspect of such queries, i.e., which objects are relevant to the user and which are not depends on the perception of the user. Query refinement is used to handle user subjectivity in similarity search systems. This paper explores how to enhance database systems with query refinement for content-based (similarity) searches in object-relational databases. Query refinement is achieved through relevance feedback where the user judges individual result tuples and the system adapts and restructures the query to better reflect the users information need. We present a query refinement framework and an array of strategies for refinement that address different aspects of the problem. Our experiments demonstrate the effectiveness of the query refinement techniques proposed in this paper.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

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.

References

  1. S. Adali, P. Bonatti, M. L. Sapino, and V. S. Subrahmanian. A multi-similarity algebra. In Proc. ACM SIGMOD98, pages 402–413, 1998.

    Google Scholar 

  2. Rakesh Agrawal and Edward L. Wimmers. A framework for expressing and combining preferences. In ACM SIGMOD, 2000.

    Google Scholar 

  3. G. Amato, F. Rabitti, and P. Savino. Multimedia document search on the web. In 7th Int. World Wide Web Conference (WWW7).

    Google Scholar 

  4. Ricardo Baeza-Yates and Ribeiro-Neto. Modern Information Retrieval. ACM Press Series/Addison Wesley, New York, May 1999.

    Google Scholar 

  5. Ilaria Bartolini, Paolo Ciaccia, and Florian Waas. Feedback bypass: A new approach to interactive similarity query processing. In 27th Very Large Databases (VLDB), Rome, Italy, September 2001.

    Google Scholar 

  6. J. P. Callan, W. B. Croft, and S. M. Harding. The inquery retrieval system. In In Proceedings of the Third International Conference on Database and Expert Systems Applications, Valencia, Spain, 1992.

    Google Scholar 

  7. Shih-Fu Chang and john R. Smith. Finding images/video in large archives. D-Lib Magazine, 1997.

    Google Scholar 

  8. Wesley W. Chu et al. CoBase: A Scalable and Extensible Cooperative Information System. Journal of Intelligent Information Systems, 6, 1996.

    Google Scholar 

  9. Ronald Fagin and Edward L. Wimmers. Incorporating user preferences in multimedia queries. In Proc of Int. Conf. on Database Theory, 1997.

    Google Scholar 

  10. M. Flickner, Harpreet Sawhney, Wayne Niblack, and Jonathan Ashley. Query by Image and Video Content: The QBIC System. IEEE Computer, 28(9):23–32, September 1995.

    Google Scholar 

  11. Norbert Fuhr. Logical and conceptual models for the integration of information retrieval and database systems. 1996.

    Google Scholar 

  12. Yoshiharu Ishikawa, Ravishankar Subramanya, and Christos Faloutsos. Mindreader: Querying databases through multiple examples. In Int’l Conf. on Very Large Data Bases, 1998.

    Google Scholar 

  13. Carlo Meghini. Fourth DELOS Workshop-Image Indexing and Retrieval. ERCIM Report, San Miniato, Pisa, Italy, August 1997.

    Google Scholar 

  14. T. P. Minka and R. W. Picard. Interactive learning using a “society of models”. Technical Report 349, MIT Media Lab, 1996.

    Google Scholar 

  15. Amihai Motro. VAGUE: A user interface to relational databases that permits vague queries. ACM TOIS, 6(3):187–214, July 1988.

    Article  Google Scholar 

  16. Michael Ortega, Yong Rui, Kaushik Chakrabarti, Kriengkrai Porkaew, Sharad Mehrotra, and Thomas S. Huang. Supporting ranked boolean similarity queries in mars. IEEE Trans. on Data Engineering, 10(6), December 1998.

    Google Scholar 

  17. Kriengkrai Porkaew, Sharad Mehrotra, Michael Ortega, and Kaushik Chakrabarti. Similarity search using multiple examples in mars. In Proc. Visual’99, June 1999.

    Google Scholar 

  18. J.J. Rocchio. Relevance feedback in information retrieval. In Gerard Salton, editor, The SMART Retrieval System, pages 313–323. Prentice-Hall, Englewood NJ, 1971.

    Google Scholar 

  19. Yong Rui, Thomas S. Huang, Michael Ortega, and Sharad Mehrotra. Relevance feedback: A power tool for interactive content-based image retrieval. IEEE CSVT, September 1998.

    Google Scholar 

  20. John C. Shafer and Rakesh Agrawal. Continuous querying in database-centric web applications. In WWW9 conference, Amsterdan, Netherlands, May 2000.

    Google Scholar 

  21. L. Wu, C. Faloutsos, K. Sycara, and T. Payne. FALCON: Feedback adaptive loop for content-based retrieval. Proceedings of VLDB Conference, 2000.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ortega-Binderberger, M., Chakrabarti, K., Mehrotra, S. (2002). An Approach to Integrating Query Refinement in SQL. In: Jensen, C.S., et al. Advances in Database Technology — EDBT 2002. EDBT 2002. Lecture Notes in Computer Science, vol 2287. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45876-X_4

Download citation

  • DOI: https://doi.org/10.1007/3-540-45876-X_4

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43324-8

  • Online ISBN: 978-3-540-45876-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics