Abstract
This chapter is devoted to a class of nonadditive set functions in the theory of generalized information measures. Besides its relevance in the context of semantic information which becomes more and more important in knowledge representation, its contents at the technical level exhibits a connection with Choquet capacity. More importantly, its principles and tools of analysis present a striking analogy with the actual investigation of fuzzy measures. This duality is interesting its own right.
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© 1995 Springer Science+Business Media Dordrecht
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Grabisch, M., Nguyen, H.T., Walker, E.A. (1995). Information Measures. In: Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference. Theory and Decision Library, vol 30. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8449-4_4
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DOI: https://doi.org/10.1007/978-94-015-8449-4_4
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4477-8
Online ISBN: 978-94-015-8449-4
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