FleSe: A Tool for Posing Flexible and Expressive (Fuzzy) Queries to a Regular Database

  • Víctor Pablos-CerueloEmail author
  • Susana Munoz-Hernandez
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 290)


We present FleSe, a tool for performing fuzzy and non-fuzzy queries to regular databases. The existing tools for querying databases have a syntax too complicate for normal users. What we present is a tool with a user-friendly interface that allows to perform any query that the underlying framework can solve. The framework is fully adaptable and configurable, so that introducing new knowledge and linking it to the information stored in databases can be done easily. We expect this work contributes to the development of more human-oriented fuzzy search engines.


fuzzy logic search engine databases 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bosc, P., Pivert, O.: Sqlf: a relational database language for fuzzy querying. IEEE Transactions on Fuzzy Systems 3(1), 1–17 (1995)CrossRefMathSciNetGoogle Scholar
  2. 2.
    Medina, J., Ojeda-Aciego, M., Vojtáš, P.: A multi-adjoint approach to similarity-based unification. Electronic Notes in Theoretical Computer Science 66(5), 70–85 (2002), uNCL 2002, Unification in Non-Classical Logics (ICALP 2002 Satellite Workshop),
  3. 3.
    Medina, J., Ojeda-Aciego, M., Vojtáš, P.: A completeness theorem for multi-adjoint logic programming. In: FUZZ-IEEE, pp. 1031–1034 (2001)Google Scholar
  4. 4.
    Medina, J., Ojeda-Aciego, M., Vojtáš, P.: Multi-adjoint logic programming with continuous semantics. In: Eiter, T., Faber, W., Truszczyński, M. (eds.) LPNMR 2001. LNCS (LNAI), vol. 2173, pp. 351–364. Springer, Heidelberg (2001)Google Scholar
  5. 5.
    Medina, J., Ojeda-Aciego, M., Vojtáš, P.: A procedural semantics for multi-adjoint logic programming. In: Brazdil, P.B., Jorge, A.M. (eds.) EPIA 2001. LNCS (LNAI), vol. 2258, pp. 290–297. Springer, Heidelberg (2001)Google Scholar
  6. 6.
    Medina, J., Ojeda-Aciego, M., Vojtáš, P.: Similarity-based unification: a multi-adjoint approach. Fuzzy Sets and Systems 146(1), 43–62 (2004)CrossRefzbMATHMathSciNetGoogle Scholar
  7. 7.
    Moreno, J.M., Ojeda-Aciego, M.: On first-order multi-adjoint logic programming. In: 11th Spanish Congress on Fuzzy Logic and Technology (2002),
  8. 8.
    Palacios, A.M., Gacto, M.J., Alcalá-Fdez, J.: Mining fuzzy association rules from low-quality data. Soft Comput. 16(5), 883–901 (2012)CrossRefGoogle Scholar
  9. 9.
    Pablos-Ceruelo, V., Muñoz-Hernández, S.: Introducing priorities in rfuzzy: Syntax and semantics. In: CMMSE 2011: Proceedings of the 11th International Conference on Mathematical Methods in Science and Engineering, Benidorm, Alicante, Spain, vol. 3, pp. 918–929 (June 2011),
  10. 10.
    Pablos-Ceruelo, V., Muñoz-Hernández, S.: Getting answers to fuzzy and flexible searches by easy modelling of real-world knowledge. In: FCTA 2013: Proceedings of the 5th International Conference on Fuzzy Computation Theory and Applications (2013)Google Scholar
  11. 11.
    Sterling, L., Shapiro, E.: The Art of Prolog. MIT Press (1987)Google Scholar
  12. 12.
    Ishizuka, M., Kanai, N.: Prolog-elf incorporating fuzzy logic. In: IJCAI 1985: Proceedings of the 9th International Joint Conference on Artificial Intelligence, pp. 701–703. Morgan Kaufmann Publishers Inc., San Francisco (1985)Google Scholar
  13. 13.
    Baldwin, J.F., Martin, T.P., Pilsworth, B.W.: Fril- Fuzzy and Evidential Reasoning in Artificial Intelligence. John Wiley & Sons, Inc., New York (1995)Google Scholar
  14. 14.
    Li, D., Liu, D.: A fuzzy Prolog database system. John Wiley & Sons, Inc., New York (1990)Google Scholar
  15. 15.
    Bobillo, F., Straccia, U.: fuzzydl: An expressive fuzzy description logic reasoner. In: 2008 International Conference on Fuzzy Systems (FUZZ 2008), pp. 923–930. IEEE Computer Society (2008)Google Scholar
  16. 16.
    Morcillo, P.J., Moreno, G.: Floper, a fuzzy logic programming environment for research. In: de Oviedo, F.U. (ed.) Proceedings of VIII Jornadas sobre Programación y Lenguajes (PROLE 2008), Gijón, Spain, pp. 259–263 (October 2008)Google Scholar
  17. 17.
    Vaucheret, C., Guadarrama, S., Muñoz-Hernández, S.: Fuzzy prolog: A simple general implementation using CLP(R). In: Baaz, M., Voronkov, A. (eds.) LPAR 2002. LNCS (LNAI), vol. 2514, pp. 450–464. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  18. 18.
    Guadarrama, S., Muñoz-Hernández, S., Vaucheret, C.: Fuzzy prolog: a new approach using soft constraints propagation. Fuzzy Sets and Systems (FSS) 144(1), 127–150 (2004); possibilistic Logic and Related IssuesGoogle Scholar
  19. 19.
    Muñoz-Hernández, S., Pablos-Ceruelo, V., Strass, H.: Rfuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over prolog. Information Sciences 181(10), 1951–1970 (2011), special Issue on Information Engineering Applications Based on Lattices,
  20. 20.
    The CLIP Lab, The Ciao Prolog Development System WWW Site,

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Víctor Pablos-Ceruelo
    • 1
    Email author
  • Susana Munoz-Hernandez
    • 1
  1. 1.The Babel Research Group, Facultad de InformáticaUniversidad Politécnica de MadridMadridSpain

Personalised recommendations