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Fuzzy Weighted Attribute Combinations Based Similarity Measures

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10369))

Abstract

Some similarity measures for fuzzy subsets are introduced: they are based on fuzzy set-theoretic operations and on a weight capacity expressing the degree of contribution of each group of attributes. For such measures, the properties of dominance and T-transitivity are investigated.

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Acknowledgment

This work was partially supported by INdAM-GNAMPA through the Project 2015 U2015/000418 and the Project 2016 U2016/000391 and by the Italian Ministry of Education, University and Research, under grant 2010FP79LR_003.

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Correspondence to Barbara Vantaggi .

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Coletti, G., Petturiti, D., Vantaggi, B. (2017). Fuzzy Weighted Attribute Combinations Based Similarity Measures. In: Antonucci, A., Cholvy, L., Papini, O. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2017. Lecture Notes in Computer Science(), vol 10369. Springer, Cham. https://doi.org/10.1007/978-3-319-61581-3_33

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  • DOI: https://doi.org/10.1007/978-3-319-61581-3_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61580-6

  • Online ISBN: 978-3-319-61581-3

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