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Issue title: Concurrency, Specification and Programming
Article type: Research Article
Authors: Gomolińska, Anna | Wolski, Marcin
Affiliations: Institute of Informatics, Białystok University, Sosnowa 64, 15-887 Białystok, Poland. [email protected] | Department of Logic and Methodology of Science, Maria Curie-Skłodowska University, pl. Maria Curie-Skłodowska 4, 20-031 Lublin, Poland. [email protected]
Note: [] Address for correspondence: Institute of Informatics, Białystok University, Sosnowa 64, 15-887 Białystok, Poland.
Abstract: Rough inclusion functions are mappings considered in rough set theory with which one can measure the degree of inclusion of a set (information granule) in a set (information granule) in line with rough mereology. On the other hand, similarity indices are mappings used in cluster analysis with which one can compare clusterings, and clustering methods with respect to similarity. In this article we show that a large number of similarity indices, known from the literature, can be generated by three simple rough inclusion functions, the standard rough inclusion function included.
Keywords: rough inclusion function, similarity index, cluster analysis, granular computing
DOI: 10.3233/FI-2014-1068
Journal: Fundamenta Informaticae, vol. 133, no. 2-3, pp. 149-163, 2014
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