Skip to main content
SpringerLink
Log in

Fuzzy Logic Based Intelligent Tool for Databases

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3682))

Abstract

In this paper, a software tool for enabling fuzzy query from a classical database is introduced. By using this tool, some fields (attribute) of a database table can be fuzzified and a supplementary database, which includes fuzzy values, is formed. Developed software tool is applied in a sample database including some fields about the students for the evaluation of scholarship application. It is concluded that, the fuzzy query method is more flexible and the results of such query are more predictive.

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

Access this chapter

Log in via an institution
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. Rasmussen, D., Yager, R.R.: Summary SQL-A Fuzzy Tool For Data Mining. In: Intelligent Data Analysis, vol. 1, Elsevier Science Inc., Amsterdam (1997)

    Google Scholar 

  2. Bosc, P., Pivert, O.: SQLf: A Relational Database Language for Fuzzy Querying. IEEE Transactions on Fuzzy Systems 3 (1997)

    Google Scholar 

  3. Cox, E.: FuzzySQL-A Tool for Finding The Truth-The Power of Approximate Database Queries. PC AI-Intelligent Applications 14 (January/February 2000)

    Google Scholar 

  4. Eminov, M.: Querying a Database by Fuzzification of Attribute Values, http://idari.cu.edu.tr/sempozyum/bil46.htm

  5. Zadeh, L.A., Kacprzyk, J.: Fuzzy Logic For The Management of Uncertainty, pp. 645–672. Library of Congress Cataloging in Publication Data Press, New York (1992)

    Google Scholar 

  6. Kacprzyk, J., Ziolkowsski, A.: Database Queries with Fuzzy Linguistic Quantifiers. IEEE Transactions on Systems, Man, And Cybernetics SMC-16, 474–479

    Google Scholar 

  7. Elmasri, R., Navathe, S.B.: Fundamentals of database systems, p. 243. Addison Wesley, Reading (2000)

    Google Scholar 

  8. Zadeh, L.A.: Fuzzy Sets. Information and Control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  9. Jamshidi, M.: Fuzzy Logic and Control: Software and Hardware Applications, pp. 16–18. PTR Prentice-Hall, Englewood Cliffs (1993)

    Google Scholar 

  10. Takahashi, Y.: Fuzzy Database Query Languages and Their Relational Completeness Theorem. IEEE Transactions on Knowledge and Data Engineering 5, 123 (1993)

    Article  Google Scholar 

  11. Li-Xin, W.: Adaptive Fuzzy Systems and Control: Design and Stability Analysis, pp. 9–14. PTR Prentice-Hall, Englewood Cliffs (1994)

    Google Scholar 

  12. Bosc, P., Prade, H.: An Introduction To the Fuzzy Set Possibility Theory-Based Treatment of Soft Queries and Uncertain or Imprecise Databases. In: Uncertainty Management in Information Systems: From Needs to Solutions, pp. 285–324. Kluwer Academic Publ., Dordrecht (1997)

    Google Scholar 

  13. Elmas, Ç.: Fuzzy Logic Control Mechanism. Seçkin, Sõhhiye, Ankara, 63 Bulanõk Mantõk Denetleyiciler. Seçkin, Sõhhiye, Ankara, 63 (2003)

    Google Scholar 

  14. Nath, A.K., Lee, T.T.: On The Design of a Classifier With Linguistic Variables As Inputs. In: Bezdek, J.C., Pal, S.K. (eds.) Fuzzy Models for Pattern Recognition: Methods That Search for Stuctures in Data, New York, pp. 242–244 (1992)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Kocaeli University, Izmit, Turkey

    Sevinc Ilhan & Nevcihan Duru

Authors
  1. Sevinc Ilhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nevcihan Duru
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, BN2 4GJ, Moulsecoomb, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ilhan, S., Duru, N. (2005). Fuzzy Logic Based Intelligent Tool for Databases. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552451_51

Download citation

  • DOI: https://doi.org/10.1007/11552451_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28895-4

  • Online ISBN: 978-3-540-31986-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation