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Soft Computing: Methodologies and Applications pp 299–309Cite as

A Realistic Information Retrieval Environment to Validate a Multiobjective GA-P Algorithm for Learning Fuzzy Queries

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Part of the book series: Advances in Soft Computing ((AINSC,volume 32))

Summary

IQBE has been shown as a promising technique to assist the users in the query formulation process. In this framework, queries are automatically derived from sets of documents provided by them. However, the different proposals found in the specialized literature are usually validated in non realistic information retrieval environments. In this work, we design several experimental setups to create real-like retrieval environments and validate the applicability of a previously proposed multiobjective evolutionary IQBE technique for fuzzy queries on them.

This work was supported by the Spanish Ministerio de Ciencia y Tecnología under projects TIC2003-07977 and TIC2003-00877, including FEDER fundings.

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References

  1. T. Bäck, D.B. Fogel, and Z. Michalewicz. Handbook of Evolutionary Computation. IOP Publishing and Oxford University Press, 1997.

    Google Scholar 

  2. R. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval. Adisson, 1999.

    Google Scholar 

  3. G. Bordogna, P. Carrara, and G. Pasi. Fuzzy Approaches to Extend Boolean Information Retrieval. In P. Bosc and J. Kacprzyk, editors, Fuzziness in Database Management Systems, pp. 231–274. 1995.

    Google Scholar 

  4. H. Chen and et al. A Machine Learning Approach to Inductive Query by Examples: An Experiment Using Relevance Feedback, ID3, Genetic Algoritms, and Simulated Annealing. Journal of the American Society for Information Science, 49(8):693–705, 1998.

    Article  Google Scholar 

  5. C._A. Coello, D. A. Van Veldhuizen, and G. B. Lamant. Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academy Publisher, 2002.

    Google Scholar 

  6. O. Cordón, E. Herrera-Viedma, and M. Luque. Evolutionary Learning of Boolean Queries by Multiobjective Genetic Programming. In Proc. PPSN-VII, pp. 710–719, Granada (Spain), 2002. LNCS 2439.

    Google Scholar 

  7. O. Cordón, F. Moya, and C. Zarco. A GA-P Algorithm to Automatically Formulate Extended Boolean Queries for a Fuzzy Information Retrieval System. Mathware & Soft Computing, 7(2–3):309–322, 2000.

    Google Scholar 

  8. O. Cordón, F. Moya, and C. Zarco. A new Evolutionary Algorithm combining Simulated Annealing and Genetic Programming for Relevance Feedback in Fuzzy Information Retrieval Systems. Soft Computing, 6(5):308–319, 2002.

    Google Scholar 

  9. O. Cordón, F. Moya, and C. Zarco. Automatic Learning of Multiple Extended Boolean Queries by Multiobjective GA-P Algorithms. In V. Loia, M. Nikravesh, and L. A. Zadeh, editors, Fuzzy Logic and the Internet. Springer, 2003. In press.

    Google Scholar 

  10. L._J. Eshelman and J. D. Schaffer. Real-coded Genetic Algorithms and Interval-Schemata. In L. D. Whitley, editor, Foundations of Genetic Algorithms 2, pp. 187–202. 1993.

    Google Scholar 

  11. W. Fan, M. D. Gordon, and P. Pathak. Personalization of Search Engine Services for Effective Retrieval and Knowledge Management. In Proceedings of the 2000 International Conference on Information Systems (ICIS), Brisbane, Australia, 2000.

    Google Scholar 

  12. L. Howard and D. D’Angelo. The GA-P: A Genetic Algorithm and Genetic Programming Hybrid. IEEE Expert, 3(10):11–15, 1995.

    Article  Google Scholar 

  13. R.R. Korfhage. Information Storage and Retrieval. Wiley, 1997.

    Google Scholar 

  14. J. Koza. Genetic Programming. On the Programming of Computers by Means of Natural Selection. The MIT Press, 1992.

    Google Scholar 

  15. D.H. Kraft, F.E. Petry, B.P. Buckes, and T. Sadasivan. Genetic Algorithms for Query Optimization in Information Retrieval: Relevance Feedback. In E. Sanchez, T. Shibata, and L.A Zadeh, editors, Genetic Algorithms and Fuzzy Logic Systems, pp. 155–173. 1997.

    Google Scholar 

  16. Z. Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, 1996.

    Google Scholar 

  17. E. Sanchez. Importance in Knowledge Systems. Information Systems, 6(14):455–464.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Computer Science and A.I. E.T.S. de Ingeniería Informática, University of Granada, 18071, Granada, Spain

    Oscar Cordón, Enrique Herrera-Viedma & María Luque

  2. Dept. of Information Sciences. Faculty of Information Sciences, University of Granada, 18071, Granada, Spain

    Felix Moya

  3. PULEVA S.A., Camino de Purchil, 66, 18004, Granada, Spain

    Carmen Zarco

Authors
  1. Oscar Cordón
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  2. Enrique Herrera-Viedma
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  3. María Luque
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  4. Felix Moya
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  5. Carmen Zarco
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Editor information

Editors and Affiliations

  1. Fakultät für Elektrotechnik und Informationstechnik, Lehrstuhl für Elektrische Steuerung und Regelung, Universität Dortmund, Otto-Hahn-Str. 4, 44227, Dortmund, Germany

    Frank Hoffmann

  2. Fraunhofer IPK, Berlin

    Mario Köppen

  3. Institut für Sicherheits-/Prüftechnik, Pascalstr. 8-9, 10587, Berlin, Germany

    Mario Köppen

  4. FH Braunschweig/Wolfenbüttel, Salzdahlumer Str. 46/48, 38302, Wolfenbüttel, Germany

    Frank Klawonn

  5. Enterprise Integration, Cranfield University, Cranfield, Bedford, MK43 0AL, UK

    Rajkumar Roy

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© 2005 Springer-Verlag Berlin Heidelberg

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Cordón, O., Herrera-Viedma, E., Luque, M., Moya, F., Zarco, C. (2005). A Realistic Information Retrieval Environment to Validate a Multiobjective GA-P Algorithm for Learning Fuzzy Queries. In: Hoffmann, F., Köppen, M., Klawonn, F., Roy, R. (eds) Soft Computing: Methodologies and Applications. Advances in Soft Computing, vol 32. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32400-3_23

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  • DOI: https://doi.org/10.1007/3-540-32400-3_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25726-4

  • Online ISBN: 978-3-540-32400-3

  • eBook Packages: EngineeringEngineering (R0)

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