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Approximating the combination of belief functions using the fast Möbius transform in a coarsened frame

✍ Scribed by Thierry Denœux; Amel Ben Yaghlane


Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
269 KB
Volume
31
Category
Article
ISSN
0888-613X

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✦ Synopsis


A method is proposed for reducing the size of a frame of discernment, in such a way that the loss of information content in a set of belief functions is minimized. This method may be seen as a hierarchical clustering procedure applied to the columns of a binary data matrix, using a particular dissimilarity measure. It allows to compute approximations of the mass functions, which can be combined efficiently in the coarsened frame using the fast M€ o obius transform algorithm, yielding inner and outer approximations of the combined belief function.