Computational Intelligence for Knowledge-Based Systems by Bernadette Bouchon-Meunier, Giulianella Coletti,


By Bernadette Bouchon-Meunier, Giulianella Coletti, Marie-Jeanne Lesot, Maria Rifqi (auth.), Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann (eds.)

The ebook constitutes the refereed lawsuits of the thirteenth overseas convention on info Processing and administration of Uncertainty in Knowledge-Based structures, IPMU 2010, held in Dortmund, Germany from June 28 - July 2, 2010. The seventy seven revised complete papers have been rigorously reviewed and chosen from 320 submissions and replicate the richness of analysis within the box of Computational Intelligence and symbolize advancements on themes as: computing device studying, info mining, trend popularity, uncertainty dealing with, aggregation and fusion of data in addition to good judgment and data processing.

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Extra resources for Computational Intelligence for Knowledge-Based Systems Design: 13th International Conference on Information Processing and Management of Uncertainty, IPMU 2010, Dortmund, Germany, June 28 - July 2, 2010. Proceedings

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This specific structure of the data has consequences on the equivalence degrees. Top-k Comparison. When focusing on top-k rankings, it can be observed that the difference between the two data types becomes less marked when k decreases. The standard deviations increase, underlying the influence of the request data especially on the beginning of the lists. Besides, although the equivalence degrees significantly decrease, the order of the measure pairs in terms of equivalence degree is not modified. Three equivalence levels can be distinguished in particular for k = 10.

E. if ∃q/∀x ∈ D |X| = q, then all similarity measures are equivalent on D. We would like to extent this study to numerical data and to the quasi-equivalence property. References 1. : Monotone equivariant cluster analysis. SIAM J. Appl. Math. 37, 148–165 (1979) 2. : Indice de similarit´e et pr´eordonnance associ´ee. In: S´eminaire sur les ordres totaux finis, Aix-en-Provence, pp. 233–243 (1967) 3. : A classification of presence/absence based dissimilarity coefficients. Journal of Classification 6, 233–246 (1989) 4.

A t-norm on L is smooth if and only if it is divisible. The next proposition characterizes all smooth t-norms on L as particular ordinal sums of copies of the t-norm of Lukasiewicz. Proposition 2. A t-norm T on L is smooth if and only if there exists J = {0 = i0 < i1 < ... < im = n} ⊆ L such that T (i, j) = max(ik , i + j − ik ) if i, j ∈ [ik , ik+1 ] for some ik ∈ J min{i, j} otherwise. im = n >. 42 3 G. Mayor and J. Recasens Finitely Valued Indistinguishability Operators Indistinguishability operators fuzzify the concepts of crisp equality and crisp equivalence relation.

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