Abstract
Rough set deals with crisp granularity of objects given a data table called information system as a pair I = (U, A), where U is a universal set of objects and A is a non-empty finite set of attributes. We may consider A as a set of contexts of attributes, where A i ∈ A is a set of attributes regarded as a context or background. Consequently, if there are n contexts in A, where A = {A 1,..., A n }, it provides n partitions. A given set of object, \( X \subseteq U \) , may then be represented into n pairs of lower and upper approximations denoted as multi-rough sets of X. Some properties and operations are proposed and examined.
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References
Komorowski, J., Pawlak, Z., Polkowski, L., Skowron, A., ‘Rough Sets: A Tutorial’, In S.K Pal and A. Skowron (Eds.), Rough Fuzzy Hybridization, (1999), pp. 3–98.
Pawlak, Z., Rough sets, International Journal Computation & Information Science, 11, (1982), pp. 341–356.
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© 2003 Springer-Verlag Berlin Heidelberg
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Intan, R., Mukaidono, M. (2003). Multi-rough Sets Based on Multi-contexts of Attributes. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_38
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DOI: https://doi.org/10.1007/3-540-39205-X_38
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