Skip to main content
SpringerLink
Log in
Book cover

International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets

IWIFSGN 2018: Uncertainty and Imprecision in Decision Making and Decision Support: New Challenges, Solutions and Perspectives pp 341–362Cite as

On the Use of Fuzzy Sets Weighted Subsethood Indicators in a Text Categorization Problem

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1081))

Abstract

The paper studies the problem of fuzzy sets subsethood in a new framework inspired by our previous work on textual information processing. The proposed algorithms for categorizing textual documents are expressed in terms of the (approximate) subsethood of representing them fuzzy sets. Here we focus on the novel aspect of such a subsethood which consists in assuming that the elements of the universe are assigned with some importance degrees. Thus when the degree of approximate subsethood of two fuzzy sets is to be determined then not only membership degrees are taken into account but also the mentioned importance degrees. We study how these importance degrees may be taken into account by a class of approximate subsethood indicators based on the calculus of linguistically quantified propositions with a special emphasis on the Kosko’s indicator.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Allan, J. (ed.): Topic Detection and Tracking: Event-Based Information. Kluwer Academic Publishers, Norwell (2002)

    MATH  Google Scholar 

  2. Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. ACM Press and Addison Wesley, New York (1999)

    Google Scholar 

  3. Bandler, W., Kohout, L.: Fuzzy power sets and fuzzy implication operators. Fuzzy Sets Syst. 4, 13–30 (1980)

    Article  MathSciNet  Google Scholar 

  4. Bordogna, G., Pasi, G.: Application of fuzzy sets theory to extend Boolean information retrieval. In: Crestani, F., Pasi, G. (eds.) Soft Computing in Information Retrieval, pp. 21–47. Physica Verlag, Heidelberg (2000)

    Chapter  Google Scholar 

  5. Bosc, P., Claveau, V., Pivert, O., Ughetto, L.: Graded-inclusion-based information retrieval systems. In: Boughanem, M., Berrut, C., Mothe, J., Soule-Dupuy, C. (eds.) Advances in Information Retrieval, pp. 252–263. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  6. Bosc, P., Pivert, O.: About approximate inclusion and its axiomatization. Fuzzy Sets Syst. 157(11), 1438–1454 (2006)

    Article  MathSciNet  Google Scholar 

  7. Bosc, P., Pivert, O.: On a reinforced fuzzy inclusion and its application to database querying. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds.) Advances on Computational Intelligence, pp. 351–360. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  8. D’Alessio, S., Murray, K.A., Schiaffino, R., Kershenbaum, A.: The effect of using hierarchical classifiers in text categorization. In: Mariani, J., Harman, D. (eds.) Computer-Assisted Information Retrieval (Recherche d’Information et ses Applications) - RIAO 2000, 6th International Conference, College de France, France, 12–14 April 2000, Proceedings, pp. 302–313. CID (2000)

    Google Scholar 

  9. Fodor, J., Roubens, M.: Fuzzy Preference Modelling and Multicriteria Decision Support. Series D: System Theory, Knowledge Engineering and Problem Solving. Kluwer Academic Publishers, Dordrecht (1994)

    Book  Google Scholar 

  10. Gajewski, M., Kacprzyk, J., Zadrożny, S.: Topic detection and tracking: a focused survey and a new variant. Informatyka Stosowana 2014(1), 133–147 (2014)

    Google Scholar 

  11. Koller, D., Sahami, M.: Hierarchically classifying documents using very few words. In: Fisher, D.H. (ed.) Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), Nashville, Tennessee, USA, 8–12 July 1997, pp. 170–178. Morgan Kaufmann (1997)

    Google Scholar 

  12. Kosko, B.: Fuzzy entropy and conditioning. Inf. Sci. 40(2), 165–174 (1986)

    Article  MathSciNet  Google Scholar 

  13. Liau, C.J., Yao, Y.: Information retrieval by possibilistic reasoning. In: Database and Expert Systems Applications. LNCS, vol. 2113, pp. 52–61. Springer (2001)

    Google Scholar 

  14. Losada, D.E., Barreiro, A.: A logical model for information retrieval based on propositional logic and belief revision. Comput. J. 44(5), 410–424 (2001)

    Article  Google Scholar 

  15. Losada, D.E., Barreiro, A.: Embedding term similarity and inverse document frequency into a logical model of information retrieval. J. Am. Soc. Inf. Sci. Technol. (JASIST) 54(4), 285–301 (2003)

    Article  Google Scholar 

  16. Omhover, J.F., Rifqi, M., Detyniecki, M.: Ranking invariance based on similarity measures in document retrieval. In: Proceedings of the Third International Conference on Adaptive Multimedia Retrieval: User, Context, and Feedback, AMR 2005, pp. 55–64. Springer, Heidelberg (2006)

    Google Scholar 

  17. Sebastiani, F.: Machine learning in automated text categorization. ACM Comput. Surv. 34(1), 1–47 (2002). https://doi.org/10.1145/505282.505283

    Article  Google Scholar 

  18. Sinha, D., Dougherty, E.R.: Fuzzification of set inclusion: theory and applications. Fuzzy Sets Syst. 55(1), 15–42 (1993)

    Article  MathSciNet  Google Scholar 

  19. Ughetto, L., Claveau, V.: Different interpretations of fuzzy gradual-inclusion-based IR models. In: Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology, pp. 431–438. Atlantis Press (2011)

    Google Scholar 

  20. Weigend, A.S., Wiener, E.D., Pedersen, J.O.: Exploiting hierarchy in text categorization. Inf. Retr. 1(3), 193–216 (1999)

    Article  Google Scholar 

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

    Article  Google Scholar 

  22. Zadeh, L.: A computational approach to fuzzy quantifiers in natural languages. Comput. Math. Appl. 9, 149–184 (1983). https://doi.org/10.1016/0898-1221(83)90013-5

    Article  MathSciNet  MATH  Google Scholar 

  23. Zadeh, L.A.: Probability measures of fuzzy events. J. Math. Anal. Appl. 23, 421–427 (1968)

    Article  MathSciNet  Google Scholar 

  24. Zadrożny, S., Kacprzyk, J.: An extended fuzzy Boolean model of information retrieval revisited. In: The 14th IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2005, pp. 1020–1025. IEEE, Reno, May 2005. https://doi.org/10.1109/FUZZY.2005.1452534

  25. Zadrożny, S., Kacprzyk, J., Gajewski, M.: A solution of the multiaspect text categorization problem by a hybrid HMM and LDA based technique. In: 16th International Conference Information Processing and Management of Uncertainty in Knowledge-Based Systems, Eindhoven, The Netherlands (2016, in press)

    Google Scholar 

  26. Zadrożny, S., Kacprzyk, J., Gajewski, M.: A new two-stage approach to the multiaspect text categorization. In: 2015 IEEE Symposium on Computational Intelligence for Human-Like Intelligence, CIHLI 2015, Cape Town, South Africa, 8–10 December 2015, pp. 1484–1490. IEEE (2015)

    Google Scholar 

  27. Zadrożny, S., Kacprzyk, J., Gajewski, M.: A novel approach to sequence-of-documents focused text categorization using the concept of a degree of fuzzy set subsethood. In: Proceedings of the Annual Conference of the North American Fuzzy Information Processing Society NAFIPS 2015 and 5th World Conference on Soft Computing 2015, Redmond, WA, USA, 17–19 August 2015 (2015)

    Google Scholar 

  28. Zadrożny, S., Kacprzyk, J., Gajewski, M.: A new approach to the multiaspect text categorization by using the support vector machines. In: De Tré, G., Grzegorzewski, P., Kacprzyk, J., Owsiński, J.W., Penczek, W., Zadrożny, S. (eds.) Challenging Problems and Solutions in Intelligent Systems, pp. 261–277. Springer, Heidelberg (2016)

    Chapter  Google Scholar 

  29. Zadrożny, S., Kacprzyk, J., Gajewski, M.: The problem of first story detection in multiaspect text categorization. In: Kulczycki, P., Kóczy, L.T., Mesiar, R., Kacprzyk, J. (eds.) Information Technology and Computational Physics, pp. 3–18. Springer, Cham (2017)

    Chapter  Google Scholar 

  30. Zadrożny, S., Kacprzyk, J., Gajewski, M.: A hierarchy-aware approach to the multiaspect text categorization problem. In: Zadeh, L.A., Yager, R.R., Shahbazova, S.N., Reformat, M.Z., Kreinovich, V. (eds.) Recent Developments and the New Direction in Soft-Computing Foundations and Applications: Selected Papers from the 6th World Conference on Soft Computing, May 22–25, 2016, Berkeley, USA, pp. 49–62. Springer, Cham (2018)

    Chapter  Google Scholar 

  31. Zadrożny, S., Nowacka, K.: Interpretation of the keywords weights in information retrieval: fuzzy logic based approaches. In: 2008 19th International Workshop on Database and Expert Systems Applications, pp. 657–661. IEEE Computer Society, September 2008

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Systems Research Institute Polish Academy of Sciences, Newelska 6, 01-447, Warsaw, Poland

    Sławomir Zadrożny, Janusz Kacprzyk & Marek Gajewski

  2. Department of Telecommunications and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, 9000, Ghent, Belgium

    Guy De Tré

Authors
  1. Sławomir Zadrożny
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Janusz Kacprzyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marek Gajewski
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guy De Tré
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sławomir Zadrożny .

Editor information

Editors and Affiliations

  1. Department of Bioinformatics and Mathematical Modelling, Bulgarian Academy of Sciences, Institute of Biophysics and Biomedical Engineering, Sofia, Bulgaria

    Krassimir T. Atanassov

  2. Department of Bioinformatics and Mathematical Modelling, Bulgarian Academy of Sciences, Institute of Biophysics and Biomedical Engineering, Sofia, Bulgaria

    Vassia Atanassova

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  4. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Andrzej Kaluszko

  5. WIT- Warsaw School of Information Technology, Warsaw, Poland

    Maciej Krawczak

  6. Polish Acadamy of Sciences, Systems Research Institute, Warsaw, Poland

    Jan W. Owsinski

  7. Intelligent Systems Laboratory, Faculty of Technical Sciences, Bourgas, Bulgaria

    Sotir Sotirov

  8. Intelligent Systems Laboratory, Prof. Assen Zlatarov University, Burgas, Bulgaria

    Evdokia Sotirova

  9. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Eulalia Szmidt

  10. Polish Academy of Sciences, Systems Research Institute, Warszawa, Poland

    Slawomir Zadrozny

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zadrożny, S., Kacprzyk, J., Gajewski, M., De Tré, G. (2021). On the Use of Fuzzy Sets Weighted Subsethood Indicators in a Text Categorization Problem. In: Atanassov, K., et al. Uncertainty and Imprecision in Decision Making and Decision Support: New Challenges, Solutions and Perspectives. IWIFSGN 2018. Advances in Intelligent Systems and Computing, vol 1081. Springer, Cham. https://doi.org/10.1007/978-3-030-47024-1_33

Download citation

Publish with us

Policies and ethics

Search

Navigation