Advertisement

Fuzzy Dominance Skyline Queries

  • Marlene Goncalves
  • Leonid Tineo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4653)

Abstract

Skyline is an important and recent proposal for expressing user preferences. While no one best row exists, Skyline discards rows which are worse on all criteria than some other and retrieves non-dominated or the best ones that match user preferences. Nevertheless, some dominated rows could be interesting to user requirement, but they will be rejected by Skyline. Dominated rows could be discriminated (or ranked) by means of user preferences, but Skyline only discards dominated ones and it does not discriminate them. SQLf is a proposal for preferences queries based on fuzzy logic that allows to discriminate rows and includes user-defined terms, such as fuzzy comparison operators. In this work, we propose to flexibilize Skyline queries using fuzzy comparison operators in order to retrieve interesting dominated rows. We also introduce an evaluation mechanism for these queries and our initial experimental study shows that this mechanism has a reasonable performance.

Keywords

Skyline SQLf Flexible Querying Fuzzy Conditions 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bosc, P., Farquhar, K., Pivert, O.: Integrating Fuzzy Queries into an Existing Database Management System: An Example. International Journal of Intelligent Systems 9, 475–492 (1994)CrossRefGoogle Scholar
  2. 2.
    Bosc, P., Pivert, O.: Some Approaches for Relational Databases Flexible Querying. International Journal of Intelligent Systems 1(34), 323–354 (1992)Google Scholar
  3. 3.
    Bosc, P., Pivert, O.: On the efficiency of the alpha-cut distribution method to evaluate simple fuzzy relational queries. Advances in Fuzzy Systems-Applications and Theory, 251–260 (1995)Google Scholar
  4. 4.
    Bosc, P., Pivert, O.: SQLf: A Relational Database Language for Fuzzy Querying. IEEE Transactions on Fuzzy Systems 3(1) (February 1995)Google Scholar
  5. 5.
    Bosc, P., Pivert, O.: SQLf Query Functionality on Top of a Regular Relational Database Management System. Knowledge Management in Fuzzy Databases, 171–190 (2000)Google Scholar
  6. 6.
    Bosc, P., Liétard, L., Pivert, O.: Evaluation of Flexible Queries: The Quantified Statement Case. In: Proceedings of IPMU, Madrid, España, pp. 1115–1122 (2000)Google Scholar
  7. 7.
    Börzsönyi, S., Kossmann, D., Stocker, K.: The Skyline operator. In: Proceedings of International Conference on Data Engineering (ICDE), pp. 421–430 (2001)Google Scholar
  8. 8.
    Cox, E.: Relational Database Queries using Fuzzy Logic. Artificial Intelligent Expert, pp. 23–29 (January 1995)Google Scholar
  9. 9.
    Godfrey, P., Shipley, R., Gryz, J.: Maximal Vector Computation in Large Data Sets. In: Proceedings of the Conference on Very Large Databases (VLDB), pp. 229–240 (2005)Google Scholar
  10. 10.
    Goncalves, M., Vidal, M.E.: Preferred Skyline: A Hybrid Approach between SQLf and Skyline. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 375–384. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  11. 11.
    Ma, Z.M., Yan, L.: Generalization of Strategies for Fuzzy Query Translation in Classical Relational Databases. Information and Software Technology 49(2), 172–180 (2007)CrossRefGoogle Scholar
  12. 12.
    Papadias, D., Tao, Y., Fu, G., Seeger, B.: An Optimal and Progressive Algorithm for Skyline Queries. In: Proceedings of ACM SIGMOD, pp. 467–478. ACM Press, New York (2003)Google Scholar
  13. 13.
    Tineo, L.: Interrogaciones Flexibles a Bases de Datos Relacionales., Trabajo de Ascenso, Universidad Simón Bolívar, Caracas, Venezuela (1998)Google Scholar
  14. 14.
    Tineo, L.: Extending the power of RDBMS for Allowing Fuzzy Quantified Queries. In: Ibrahim, M., Küng, J., Revell, N. (eds.) DEXA 2000. LNCS, vol. 1873, pp. 407–416. Springer, Heidelberg (2000)Google Scholar
  15. 15.
    Tineo, L.: Una Contribución a la Interrogación Flexible de Bases de Datos: Evaluación de Consultas Cuantificadas Difusas, Tesis Doctoral, Universidad Simón Bolívar (2006)Google Scholar
  16. 16.
    Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)zbMATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Marlene Goncalves
    • 1
  • Leonid Tineo
    • 1
  1. 1.Universidad Simón Bolívar, Departamento de Computación, Apartado 89000, Caracas 1080-AVenezuela

Personalised recommendations