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      Dialectics of Knowledge Representation in a Granular Rough Set Theory

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          Abstract

          The concepts of rough and definite objects are relatively more determinate than those of granules and granulation in general rough set theory (RST) [1]. Representation of rough objects can however depend on the dialectical relation between granulation and definiteness. In this research, we make this exact in the context of RST over proto-transitive approximation spaces. This approach can be directly extended to many other types of RST. These are used for formulating an extended concept of knowledge interpretation (KI)(relative the situation for classical RST) and the problem of knowledge representation (KR) is solved. These will be of direct interest in granular KR in RST as developed by the present author [2] and of rough objects in general. In [3], these have already been used for five different semantics by the present author. This is an extended version of [4] with key examples and more results.

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          Most cited references5

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          Reliable circuits using less reliable relays

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            Information granulation and rough set approximation

            Y. Yao (2001)
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                Author and article information

                Journal
                2012-12-28
                2013-03-23
                Article
                1212.6519
                14bbc0eb-181a-494e-920e-0d295f9558b4

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                06Axx, 03G25, 03B60, 08B20, 68U35
                Enlarged version of Refereed Conference Paper. 18 pp 1 figure. (An extended version is to appear soon)
                cs.AI cs.LO

                Theoretical computer science,Artificial intelligence
                Theoretical computer science, Artificial intelligence

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