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Fuzzy Sets-Based Retranslation of Numerical Data in E-Learning

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Advances in Web Intelligence (AWIC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3528))

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Abstract

Since e-learning is becoming more and more popular, there is a need to improve and widen information techniques that support e-teachers. Presently, the automated and intelligent examining procedures are essential for this support. We present the new soft-computing procedures of rating e-tests in German. The clou of this paper is the retranslation algorithm transforming raw numerical data into human consistent terms. The retranslation associated with fuzzy template matching is supposed to be a reliable solution giving satisfactory outputs. The results of the retranslation process are expressed in natural language, which makes them understandable and useful also for technologically non-advanced personnel.

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References

  1. Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets and Systems 20, 87–96 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  2. Bandemer, H., Gottwald, S.: Fuzzy Sets, Fuzzy Logic, Fuzzy Methods with Applications. John Wiley & Sons, Chichester (1995)

    MATH  Google Scholar 

  3. Goguen, J.: L-fuzzy sets. Journal Math. Anal. Appl. 18, 145–174 (1967)

    Article  MATH  MathSciNet  Google Scholar 

  4. Gorzalczany, M.B.: A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets and Systems 21, 1–17 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  5. Karnik, N.N., Mendel, J.M.: Type-2 Fuzzy Logic Systems. IEEE Transactions on Fuzzy Systems 7(6), 643–658 (1999)

    Article  Google Scholar 

  6. Niewiadomski, A.: Intuitionistic fuzzy sets in text document comparison. PhD Dissertation, Institute of Systems Research, Polish Academy of Sciences, Warsaw, Poland (2001) (in Polish )

    Google Scholar 

  7. Niewiadomski, A., Bartyzel, M., Szczepaniak, P.S.: Linguistic Summaries of Databases in Evaluating Algorithms for Automated Distance Testing (in Polish, in print)

    Google Scholar 

  8. Niewiadomski, A., Grzybowski, R.: Fuzzy measures of text similarity in automated evaluation of exams tests. Theoretical and Applied Computer Science 5, 193–200 (2003) (in Polish)

    Google Scholar 

  9. Niewiadomski, A., RybusiƄski, B., Sakowski, K., Grzybowski, R.: The application of multivalued similarity relations to automated evaluation of grammar tests. In: Academy On-line — e-learning, methodics, technologies, management (to appear; in Polish)

    Google Scholar 

  10. Niewiadomski, A., Szczepaniak, P.S.: Fuzzy Similarity in E-Commerce Domains. In: Segovia, J., Szczepaniak, P.S., NiedĆșwiedziƄski, M. (eds.) E-Commerce and Intelligent Methods, pp. 96–102. Springer, Heidelberg (2002)

    Google Scholar 

  11. Ross, T.J.: Fuzzy Logic with Engineering Applications. McGraw-Hill, New York (1995)

    MATH  Google Scholar 

  12. Sengupta, A., Pal, T.K., Chakraborty, D.: Interpretation of inequality constraints involving interval cooeficients and a solution to interval linear programming. Fuzzy Sets and Systems 119, 129–138 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  13. Turksen, I.B.: Interval-valued fuzzy sets based on normal forms. Fuzzy Sets and Systems 20, 191–210 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  14. Zadeh, L.A.: Fuzzy Sets. Information and Control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  15. Zadeh, L.A.: The concept of linguistic variable and its application for approximate reasoning (I). Information Science 8, 199–249 (1975)

    Article  MathSciNet  Google Scholar 

  16. 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 

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Niewiadomski, A., RybusiƄski, B. (2005). Fuzzy Sets-Based Retranslation of Numerical Data in E-Learning. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds) Advances in Web Intelligence. AWIC 2005. Lecture Notes in Computer Science(), vol 3528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11495772_54

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  • DOI: https://doi.org/10.1007/11495772_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26219-0

  • Online ISBN: 978-3-540-31900-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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