Enhancing query processing of information systems | SpringerLink
Skip to main content

Enhancing query processing of information systems

  • Communications Session 5A Intelligent Information Systems
  • Conference paper
  • First Online:
Foundations of Intelligent Systems (ISMIS 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1079))

Included in the following conference series:

Abstract

Current database and information systems only provide for inflexible query processing. In this paper we have developed techniques for supporting the answering of inadequate queries to information systems introducing certain level of intelligence and flexibility. Our approach uses the notion of α-cut in fuzzy set theory to provide acceptable approximate answers for a given inadequate query. We illustrate the proposed α-cut approach for a variety of different queries which may involve different types of selection conditions. The selection conditions considered may contain fuzzy terms measured on a numeric, nominal or linguistic scale. They may employ one or more linguistic hedges of (very), or of (fairly) for query modification. Fuzzy numbers and fuzzy intervals are introduced as representations of selection conditions of inadequate queries. It is not essential to construct extensive metadata into the existing database to implement the proposed approach. A user friendly system which makes use of the proposed theory has been developed. It can support selection conditions that contain linguistic hedges of (very) and (fairly), comparators (approximately), (more-than) and (less-than), and terms that are numeric, nominal or linguistic. The test results bear positive evidence to the ease of implementation of the proposed approach.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  • Andreasen, T. and Pivert, O. 1994. ‘On the weakening of fuzzy relational queries'. In Z. Ras and M Zemankova (eds.) LNCS/LNAI 869 Proc. Methodologies for Intelligent Systems, 8th Int. Sym, ISMIS'94, Charlotte, NC, USA, October. Springer-Verlag.

    Google Scholar 

  • Bandemer, H. and Nather, W. 1992. Fuzzy Data Analysis. Doredrecht, Kluer Academic Publishers.

    Google Scholar 

  • Bezdek, J. C. and Pal, S. K. 1992. Fuzzy Models for Pattern Recognition. Piscataway, NJ, IEEE Press.

    Google Scholar 

  • Chu, W. W. and Chen, Q. 1992. ‘Neighbourhood and associative query answering'. In Journal of Intelligent Information System, 1, pp.355–382.

    Google Scholar 

  • Cuppens, F. and Demolombe, R. 1988. ‘Co-operative answering: a methodology to provide intelligent access to databases'. L. Kerschberg (ed.) Proc. 2nd Int. Conf. on Expert Database Systems, Virginia, April, pp.333–353.

    Google Scholar 

  • Dubois, D., Prade, H. and Yager, R. 1993. Fuzzy Sets for Intelligent Systems. Morgan Kaufmann, California.

    Google Scholar 

  • Loo, S. L. 1992. ‘A taxonomy for an intelligent database'. In B. Srinivasan and J. Zeleznikow, eds. Research and Practical Issues in Databases, Proc. of the 3rd Australian Database Conf. Melbourne, Australia, February, World Scientific, pp.344–355.

    Google Scholar 

  • Loo, S. L., Dillon, T. and Zeleznikow, J. 1990. ‘Intelligent accessing of database with inadequate and incomplete queries'. In Proc. Int. Conf. on Systems Management'90 — The Impact of Information Technology on Systems Management, 11–18 June 1990, Hong Kong, pp.248–253.

    Google Scholar 

  • Loo, S. L., Dillon, T., Zeleznikow, J. and Lee, K. H. 1994. ‘Two approaches for answering inadequate queries — Empirical project IDB-KROOM'. In Proc. Workshop Flexible Query Answering System'94, Copenhagen, November, Roskilde University Press, pp.127–146.

    Google Scholar 

  • Marks II, R. J. (ed.) 1994. Fuzzy Logic Technology and Applications. The Institute of Electrical and Electronic Engineers, Inc., New York.

    Google Scholar 

  • Motro, A. 1988. ‘VAGUE: A User Interface to Relational Databases that Permits Vague Queries'. ACM Trans. on Office Information Sys., 6(3), July, pp. 187–214.

    Google Scholar 

  • Zadeh, L. A. 1965. ‘Fuzzy sets'. In Information and Control, V8.3, June, pp.338–353.

    Google Scholar 

  • Zadeh, L. A. 1973. ‘Outline of a new approach to the analysis of complex systems and decision processes'. In IEEE Transactions on Systems, Man And Cybernetics, SMC-3, pp.28–44.

    Google Scholar 

  • Zadeh, L. A. 1978. ‘Fuzzy sets as a basis for the theory of possibility'. In Fuzzy Sets and Systems, 1, pp.3–28.

    Google Scholar 

  • Zimmermann, H. J. 1991. Fuzzy Set Theory — and Its Applications. d2nd revised ed. Boston, Kluwer Academic Publishers.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Zbigniew W. Raś Maciek Michalewicz

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Loo, G.S., Dillon, T., Zeleznikow, J., Lee, KH. (1996). Enhancing query processing of information systems. In: Raś, Z.W., Michalewicz, M. (eds) Foundations of Intelligent Systems. ISMIS 1996. Lecture Notes in Computer Science, vol 1079. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61286-6_163

Download citation

  • DOI: https://doi.org/10.1007/3-540-61286-6_163

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61286-5

  • Online ISBN: 978-3-540-68440-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics