Abstract
Rough mereology allows for similarity measures (called rough inclusions) which in turn form a basis for the mechanism of granulation of knowledge. Granules of knowledge, defined as classes of satisfactorily similar objects, can be regarded as worlds in which properties of entities are evaluated. Obtained in this way granular rough mereological intensional logics reveal essential properties of rough set based reasoning. We present in this work the essential facts about these logics.
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Polkowski, L., Semeniuk–Polkowska, M. (2008). Reasoning about Concepts by Rough Mereological Logics. In: Wang, G., Li, T., Grzymala-Busse, J.W., Miao, D., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2008. Lecture Notes in Computer Science(), vol 5009. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79721-0_31
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DOI: https://doi.org/10.1007/978-3-540-79721-0_31
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