Abstract
One important issue of uncertain or fuzzy object-oriented models is that uncertain membership degrees of an object to the classes in a class hierarchy may be obtained from different sources while they are actually constrained by the subclass relation. In this paper we present the notion of admissible combination functions and an algorithm to propagate and combine prior uncertain membership degrees on a class hierarchy,which are possibly conflicting, in order to produce a tightly consistent uncertain membership assignment. We assume uncertain membership degrees to be measured by support pairs represented by sub-intervals of [0,1]. The usual probabilistic interval intersection, Dempster-Shafer, and possibilistic combination rules are examined and proved to be admissible ones.
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Cao, T.H., Huynh, VN. (2010). Combination of Uncertain Class Membership Degrees with Probabilistic, Belief, and Possibilistic Measures. In: Huynh, VN., Nakamori, Y., Lawry, J., Inuiguchi, M. (eds) Integrated Uncertainty Management and Applications. Advances in Intelligent and Soft Computing, vol 68. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11960-6_36
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DOI: https://doi.org/10.1007/978-3-642-11960-6_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11959-0
Online ISBN: 978-3-642-11960-6
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