Skip to main content
Springer Nature Link
Log in

Methods of Evaluating Degrees of Truth for Linguistic Summaries of Data: A Comparative Analysis

  • Conference paper
Artificial Intelligence and Soft Computing (ICAISC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6113))

Included in the following conference series:

  • 1782 Accesses

Abstract

The paper, like some of our previous publications, focuses on linguistic summaries of databases in the sense of Yager [1], with further modifications by Kacprzyk and Yager [2]. In particular, we are interested in some alternative methods of evaluating degrees of truth, DTs, for linguistic summaries. The considered methods, for instance, Sugeno integral, GD method, or MVCP, are alternatives for ,,traditional” DTs, by Zadeh [3]. Our original contribution is an analysis of these methods and their interpretation in terms of linguistic summarization of databases. Especially, different DTs for a summary are evaluated and the computational cost is assessed. Based on that, sensitivity of the methods to different parameters of linguistic summaries, e.g. increasing number of qualifiers or the first/the second form, single/composed summarizers, relative/absolute/coherent quantifiers, are examined.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Yager, R.R.: A new approach to the summarization of data. Information Sciences 28, 69–86 (1982)

    Article  MATH  MathSciNet  Google Scholar 

  2. Kacprzyk, J., Yager, R.R.: Linguistic summaries of data using fuzzy logic. International Journal of General Systems 30, 133–154 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  3. Zadeh, L.A.: A computational approach to fuzzy quantifiers in natural languages. Computers and Maths with Applications 9, 149–184 (1983)

    Article  MATH  MathSciNet  Google Scholar 

  4. De Luca, A., Termini, S.: A definition of the non-probabilistic entropy in the setting of fuzzy sets theory. Information and Control 20, 301–312 (1972)

    Article  MATH  MathSciNet  Google Scholar 

  5. Delgado, M., Sanchez, D., Vila, M.A.: Fuzzy cardinality based evaluation of quantified sentences. International Journal of Approximate Reasoning 23, 23–66 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  6. Kacprzyk, J., Wilbik, A., Zadrożny, S.: Linguistic summaries of time series via a quantifier based aggregation using the Sugeno integral. In: 2006 IEEE International Conference on Fuzzy Systems, pp. 713–719 (2006)

    Google Scholar 

  7. Yager, R.R.: On ordered weighted averaging operators in multicriteria decision making. IEEE Transactions on Systems, Man and Cybernetics 18, 183–190 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  8. http://nsidc.org/data/docs/noaa/g02141_esdimmet/

Download references

Author information

Authors and Affiliations

  1. Institute of Information Technology, Technical University of Łódź, Poland

    Adam Niewiadomski & Oskar Korczak

Authors
  1. Adam Niewiadomski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Oskar Korczak
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Academy of Humanities and Economics in Łódź,, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Rafał Scherer

  3. Institute of Automatics,, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA,  

    Lotfi A. Zadeh

  5. Computational Intelligence Laboratory Department of Electrical and Computer Engineering, University of Louisville, 40292, Louisville, KY

    Jacek M. Zurada

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Niewiadomski, A., Korczak, O. (2010). Methods of Evaluating Degrees of Truth for Linguistic Summaries of Data: A Comparative Analysis. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13208-7_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-13208-7_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13207-0

  • Online ISBN: 978-3-642-13208-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation