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User-Friendly Interface for Introducing Fuzzy Criteria into Expressive Searches

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Intelligent Systems and Applications (IntelliSys 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1037))

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Abstract

We present a framework that allows any user (without the need of neither technical no theoretical knowledge) to define fuzzy criteria based on the non-fuzzy information stored in databases in an easy way. The interests for developing such a framework is to provide a human-oriented (fuzzy and non-fuzzy) search engine with a user-friendly interface to perform expressive and flexible searches over databases. We achieved this task by providing an intelligent interface for the users to define fuzzy criteria without having any knowledge about its low-level syntax or implementation details. Our framework allows users to pose different queries (combining crisp and fuzzy search criteria) over various conventional and modern data formats such as JSON, SQL, Prolog, CSV, XLS and XLSX. We believe our approach adds to the advancement for more intelligent and human-oriented fuzzy search engines.

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References

  1. Zadeh, L.A.: Fuzzy logic. Computer 21(4), 83–93 (1988). https://doi.org/10.1109/2.53

    Article  Google Scholar 

  2. Bosc, P., Pivert, O.: Sqlf: a relational database language for fuzzy querying. IEEE Trans. Fuzzy Syst. 3(1), 1–17 (1995)

    Article  Google Scholar 

  3. Dubois, D., Prade, H.: Using fuzzy sets in flexible querying: why and how? In: Andreasen, T., Christiansen, H., Larsen, H.L. (eds.) Flexible Query Answering Systems, Norwell, MA, USA, pp. 45–60 (1997)

    Google Scholar 

  4. Vojtáš, P.: Fuzzy logic programming. Fuzzy Sets Syst. 124(3), 361–370 (2001)

    Article  MathSciNet  Google Scholar 

  5. 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)

    Article  Google Scholar 

  6. Baldwin, J.F., Martin, T.P., Pilsworth, B.W.: Fril - Fuzzy and Evidential Reasoning in Artificial Intelligence. Wiley, New York (1995)

    Google Scholar 

  7. Li, D., Liu, D.: A Fuzzy Prolog Database System. Wiley, New York (1990)

    Google Scholar 

  8. Morcillo, P.J., Moreno, G.: FLOPER, a fuzzy logic programming environment for research. In: de Oviedo, F.U. (ed.) Proceedings of VIII Jornadas sobre Programacion y Lenguajes (PROLE 2008), Gijón, Spain, pp. 259–263, October 2008

    Google Scholar 

  9. Vaucheret, C., Guadarrama, S., Muñoz-Hernández, S.: Fuzzy prolog: a simple general implementation using CLP(R). In: Baaz M., Voronkov A. (eds.) LPAR. Lecture Notes in Artificial Intelligence, vol. 2514, pp. 450–464. Springer (2002)

    Google Scholar 

  10. Guardarrama, S., Muñoz-Hernández, S., Vaucheret, C.: Fuzzy Prolog: a new approach using soft constraints propagation. Fuzzy Sets Syst. 144(1), 127–150 (2004)

    Article  MathSciNet  Google Scholar 

  11. Muñoz-Hernández, S., Pablos-Ceruelo, V., Strass, H.: RFuzzy: syntax, semantics and implementation details of a simple and expressive fuzzy tool over prolog. Inf. Sci. 181(10), 1951–1970 (2011)

    Article  MathSciNet  Google Scholar 

  12. Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)

    Article  Google Scholar 

  13. Pablos-Ceruelo, V., Muñoz-Hernández, S.: Getting answers to fuzzy and flexible searches by easy modeling of real-world knowledge. In: IJCCI 2013 – Proceedings of the 5th International Joint Conference on Computational Intelligence (2013)

    Google Scholar 

  14. Pablos-Ceruelo, V., Muñoz-Hernández, S.: FleSe: a tool for posing flexible and expressive (fuzzy) queries to a regular database. In: Proceedings of the 11th International Conference on Distributed Computing and Artificial Intelligence, pp. 157–164 (2014)

    Google Scholar 

  15. The CLIP Lab: The Ciao Prolog Development System WWW Site. http://www.clip.dia.fi.upm.es/Software/Ciao/

  16. Medina, J., Ojeda-Aciego, M., Vojtáš, P.: A procedural semantics for multi-adjoint logic programming. In: Proceedings of Progress in Artificial Intelligence, pp. 290–297 (2001)

    Chapter  Google Scholar 

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Authors and Affiliations

  1. Universidad Politécnica de Madrid, Escuela Técnica Superior de Ingenieros Informáticos, Campus de Montegancedo s/n, 28660 Boadilla del Monte, Madrid, Spain

    Mohammad Halim Deedar & Susana Muñoz-Hernández

Authors
  1. Mohammad Halim Deedar
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  2. Susana Muñoz-Hernández
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Corresponding author

Correspondence to Mohammad Halim Deedar .

Editor information

Editors and Affiliations

  1. School of Computing, Computer Science Research Institute, Ulster University, Newtownabbey, UK

    Yaxin Bi

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

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Deedar, M.H., Muñoz-Hernández, S. (2020). User-Friendly Interface for Introducing Fuzzy Criteria into Expressive Searches. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1037. Springer, Cham. https://doi.org/10.1007/978-3-030-29516-5_74

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