Skip to main content

Using Contextual Fuzzy Views to Query Imprecise Data

  • Conference paper
  • First Online:
Database and Expert Systems Applications (DEXA 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1677))

Included in the following conference series:

Abstract

This work is concerned with the expression of querying using fuzzy values and with the storage and handling of imprecise information. This article introduces the concept of contextual fuzzy view based on the fuzzy logic theory and on case based reasoning system. The concept of contextual fuzzy view provides (i) a way to encapsulate the flexibility management induced by fuzzy querying, (ii) an optimisation of fuzzy filtering processing time, (iii) an enlargement of users’ preferences, (iv), in addition to the nearest data, an estimation of values that may be computed thanks to statistical models incorporated in case based reasoning system. The concept of contextual fuzzy view has been implemented in a prototype called CFQ written in Java language. This research takes place within a project to build a tool for the analysis of microbial risks in food products. An example of an application using CFQ is presented in the field of microbial risk assessment.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

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.

Similar content being viewed by others

References

  1. Augustin J.C. Résistance de Listeria monocytogenes aux traitements physiques. Pathologie-Biologie, vol 44, No9, pp 790–807, November 1996.

    Google Scholar 

  2. Bosc P., Lietard L., Pivert O. Soft querying, a new feature for database management system. DEXA’94 LNCS 856, 1994 pp 631–640.

    Google Scholar 

  3. Bosc P., Pivert O. SQLf: a relational database language for fuzzy querying. IEEE Transactions on fuzzy systems, vol 3, no 1, February 1995, pp 1–17.

    Article  MathSciNet  Google Scholar 

  4. Bosc P., Pivert O. On the comparison of imprecise values in fuzzy databases. Proceedings of FUZZ-IEEE’97, pp 707–712. Barcelona, 1997.

    Google Scholar 

  5. Bosc P., Pivert O. On representation-based querying of databases containing ill-known values. Proceedings of ISMIS’97, Charlotte, USA, pp 477–486, 1997.

    Google Scholar 

  6. Bosc P., Pivert O. A new approach to the filtering of ill-known data. Proceedings of FUZZ-IEEE’98, pp 1308–1313. Anchorage

    Google Scholar 

  7. Chen G.Q., Kerre E.E., Vandenbulcke, J. A general treatment of data redundancy in a fuzzy relational data model. Journal of the American Society for Information Science, 43: pp 304–311, 1992.

    Article  Google Scholar 

  8. Cubero J.C., Vila M.A. A new definition of fuzzy functional dependency in fuzzy relational databases. Journal of Intelligent Systems, 9: pp 441–448, 1994.

    Article  Google Scholar 

  9. D. Dubois, H. Prade, C. Testemale. Weighted fuzzy pattern matching. Fuzzy Sets and Systems, vol. 28, pp 313–331. 1988.

    Article  MATH  MathSciNet  Google Scholar 

  10. Foo N., Garner B.J., Rao A., Tsui E. Semantic distance in conceptual graphs. Proceeding of the 4th annual workshop on conceptual structures, pp 1–9. 1989.

    Google Scholar 

  11. Galindo J., Cubero J.C., Pons O., Medina J.M. A server for fuzzy SQL queries. Proceedings of the 1998 workshop FQAS’98 (Flexible Query-Answering Systems), Roskilde, Denmark, pp 161–171, May 1998.

    Google Scholar 

  12. Gil M. A. Modelling and analysing fuzzy elements in statistics. Proceedings of LFA 98 (Rencontres françaises sur la Logique Floue et ses Applications), Rennes, France, pp 187–200. November 1998.

    Google Scholar 

  13. Mille A., Napoli A. Aspects du raisonnement á partir de cas. PRC-GDR IA’97, pp 261–284.

    Google Scholar 

  14. Prade H. Lipski’s approach to incomplete information data bases restated and generalized in the setting of Zadeh’s possibility theory. Information Systems. Vol. 9, No1, pp. 27–42, 1984.

    Google Scholar 

  15. Prade H., Testemale C. Generalizing database relational algebra for the treatment of incomplete or uncertain information and vague queries. Information Sciences, 34: pp 115–143, 1984.

    Google Scholar 

  16. Prade H., Testemale C. Fuzzy relational databases: representational issues and reduction using similarity measures. Journal of the American Society for Information Science. 38(2): pp118–126, 1987.

    Google Scholar 

  17. Rosso L. Convenient model to describe the combined effects of temperature and pH on microbial growth. Applied and Environmental Microbiology, 61(2), pp. 610–616.

    Google Scholar 

  18. Rozier, Larlier, Bolnot. Bases microbiologiques de l’hygiène des aliments. Séporic Edition, pp 55–63.

    Google Scholar 

  19. Salotti S., Filtrage flou et représentation centrée-objet pour raisonner par analogie: le système FLORAN. Thèse de l’Université Paris XI Orsay. December 1992.

    Google Scholar 

  20. Umano M. FREEDOM-0: a fuzzy database system. Fuzzy Information and Decision Processes. Eds M. Gupta and E. Sanchez (Amsterdam: North-Holland). pp 339–347, 1982.

    Google Scholar 

  21. Zadeh L.A. Fuzzy sets as basis for a theory of possibility. Fuzzy Sets and Systems, vol. 1, pp 3–28. 1978.

    Article  MATH  MathSciNet  Google Scholar 

  22. Zadrozny S., Kacprzyk J. Implementing fuzzy querying via the internet/WWW: Java applets, activeX controls and cookies. Proceedings of the 1998 workshop FQAS’98 (Flexible Query-Answering Systems), Roskilde, Denmark, pp 358–369, May 1998.

    Google Scholar 

  23. Zemankova-Leech M., Kandel A. Fuzzy relation databases-a key to expert systems, (Köln: Verlag TÜV Rheinland), 1984. 1998.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Buche, P., Loiseau, S. (1999). Using Contextual Fuzzy Views to Query Imprecise Data. In: Bench-Capon, T.J., Soda, G., Tjoa, A.M. (eds) Database and Expert Systems Applications. DEXA 1999. Lecture Notes in Computer Science, vol 1677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48309-8_43

Download citation

  • DOI: https://doi.org/10.1007/3-540-48309-8_43

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66448-2

  • Online ISBN: 978-3-540-48309-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics