Abstract
Rough set theory depending upon deterministic information systems or knowledge bases is now becoming a mathematical foundation of soft computing. In this paper, we pick up nondeterministic knowledge bases with incomplete and selective information. The both information are given as a set of attribute values, whose difference comes from the temporal concept. If the information is referring the past information then we see it incomplete information. On the other hand, selective information means that the real attribute value is not decided in a set, i.e., we can select the most proper value from this set. By introducing these two information into knowledge bases, we develop another framework for nondeterministic knowledge bases. Namely, we discuss question-answering, approximation, rough set concept and dependencies of attributes on this nondeterministic knowledge bases.
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© 1998 Springer-Verlag Berlin Heidelberg
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Sakai, H. (1998). Some Issues on Nondeterministic Knowledge Bases with Incomplete and Selective Information. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_58
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DOI: https://doi.org/10.1007/3-540-69115-4_58
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