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Titlebook: Rough Sets, Fuzzy Sets and Knowledge Discovery; Proceedings of the I Wojciech P. Ziarko Conference proceedings 1994 British Computer Societ

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Automated Discovery of Empirical Laws in a Science Laboratory,in two main directions: (1) automated scientific discovery and (2) knowledge discovery in databases. The latter is focused on data which are fixed, prearranged and typically sparse. Because data available in databases are different from data which can be obtained by an experimental scientist, both t
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Rough Set Analysis of Multi-Attribute Decision Problems, about prescription of some decisions basing on analysis of a decision situation. In this paper, four classes of multi-attribute decision problems are defined, depending on a structure of their representation, their interpretation and the kind of questions related, as well as the rough set methodolo
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A Note on Categories of Information Systems,or example the logical kit of Semadeni [2], the information system of Pawlak [1], the context of Wille [3] and the probably most commonly known and applied relational database model of Codd [7]. From some points of view the above notions are equivalent or inter-translatable (see e.g. Wiweger [4], wh
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On Rough Sets in Topological Boolean Algebras,zations of his constructions which were offered by Wiweger [7]. One of the most important results of this note is a characterization of the rough sets determined by regular open and regular closed elements.
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Automated Discovery of Empirical Laws in a Science Laboratory,covery in databases have been described in several collections of papers, typically conference proceedings, edited by Piatetsky-Shapiro (1991, 1993), Piatetsky-Shapiro & Frawley (1991), Zytkow (1992), Ras (1993), Ziarko (1993), and many other papers.
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