Some algorithms for evaluating fuzzy relational queries

  • P. Bosc
  • O. Pivert
8. Uncertainty In Intelligent Systems
Part of the Lecture Notes in Computer Science book series (LNCS, volume 521)


An important issue in extending DBMS functionnalities is to allow the expression and execution of flexible queries in order to make these systems able to satisfy user needs more closely. To deal with this problem it is necessary to define new evaluation methods since standard (crisp) algorithms and access paths have proved to be inappropriate. A challenge in solving this problem is to keep the additional costs entailed by these new querying capabilities at a reasonable level. For this purpose we propose a set of query evaluation algorithms based on techniques expected on the one hand to restrict the amount of tuples to be transferred from disk to main memory and on the other hand to limit the computations which apply to these tuples. This work only concerns the evaluation of basic extended relational operators and may be seen as a first step towards the design of a fuzzy query optimizor. For each of the proposed methods, we suggest some useful measures for determining to what extent the corresponding algorithms are acceptable. Finally, we present an experimental framework for measuring the performance of these algorithms.


DBMS imprecise queries query processing 


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  1. Bitton D., Dewitt D.J., Turbyfill C. (1983) Benchmarking database systems: a systematic approach, Proc. VLDB Conference, pp 8–19.Google Scholar
  2. Blasgen M.W., Eswaran K.P. (1976) On the evaluation of queries in a relational database system, IBM Systems Journal, vol 16, pp 363–377.Google Scholar
  3. Bosc P., Galibourg M. (1988a) Flexible selection among objects: a framework based on fuzzy sets, Proc. SIGIR Conference, pp 433–449.Google Scholar
  4. Bosc P., Galibourg M., Hamon G. (1988b) Fuzzy querying with SQL: extensions and implementation aspects, Fuzzy sets and systems 28, pp 333–349.CrossRefMathSciNetGoogle Scholar
  5. Bosc P, Pivert O. (1989) Algorithms for flexible selection in relational databases, Proc 10th ASLIB Conference (G-B), pp 211–226.Google Scholar
  6. Bosc P., Pivert O. (1991) Fuzzy querying in conventional databases, to appear in "Fuzzy logic for the management of uncertainty" (L. Zadeh & J. Kacprzyk eds).Google Scholar
  7. Dubois D., Prade H. (1982) A unifying view of comparison indices in a fuzzy set theoritic framework, in "Fuzzy set and possibility theory" (R. Yager ed.).Google Scholar
  8. Jarke M., Koch J. (1984) Query optimization in database systems, ACM Computing Surveys, vol 16, no 2, pp 111–152.CrossRefGoogle Scholar
  9. Radecki T. (1982) Generalized boolean methods of information retrieval, International Journal of Man-Machine Studies, vol 18.Google Scholar
  10. Selinger P.G. et al. (1979) Access path selection in a relational database management system, Proc. of ACM SIGMOD Conference, pp 23–34.Google Scholar
  11. Stonebraker M. et al. (1976) The design and implementation of INGRES, ACM Transactions on Database Systems, vol 1, no 3, pp 189–222.CrossRefGoogle Scholar
  12. Tahani V. (1976) A fuzzy model of document retrieval systems, Information Processing & Management, vol 12, pp 177–187.Google Scholar
  13. Zadeh L.A. (1983) A computational approach to fuzzy quantifiers in natural languages, Computers and Mathematics, vol 9, pp 149–184.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • P. Bosc
    • 1
  • O. Pivert
    • 1
  1. 1.IRISA/ENSSATLannionFrance

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