Rough Inclusion Functions and Similarity Indices

• Autorzy: Gomolińska, A. , Wolski, M.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

rough inclusion function; similarity index; cluster analysis; granular computing

• Czasopismo: Fundamenta Informaticae
• Rocznik: 2014
• Tom: Vol. 133, nr 2/3
• Strony: 149--163
• Opis fizyczny: Bibliogr. 49 poz.

Twórcy

autor

Gomolińska, A.

• Institute of Informatics Białystok University, Sosnowa 64, 15-887 Białystok, Poland,

autor

Wolski, M.

• Department of Logic and Methodology of Science, Maria Curie-Skłodowska University, pl. Maria Curie-Skłodowska 4, 20-031 Lublin, Poland,

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Identyfikatory

DOI

10.3233/FI-2014-1068