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Granular Computing, Computer Security andWeb Intelligence
30th Annual International Computer Software and Applications Conference (COMPSAC'06), 2006What is granular computing? As the author have said in (T.Y. Lin, 2006): There are no mathematically valid formal definitions yet. Informally, any computing theory/technology that involves elements and granules (generalized subsets) may be called granular computing (GrC). Intuitively, elements are the data, and granules are the basic knowledge.
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2017
This chapter introduces a rough-granular computing approach defined for relational data. The core of this approach is the tolerance rough set model that is adapted to data stored in a relational databases. The chapter also defines a range of similarity measures for relational data.
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This chapter introduces a rough-granular computing approach defined for relational data. The core of this approach is the tolerance rough set model that is adapted to data stored in a relational databases. The chapter also defines a range of similarity measures for relational data.
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Granular computing biapproximation spaces
2005 IEEE International Conference on Granular Computing, 2005The purpose of the present work is to construct a new method for approximation of sets using two information systems simultaneously. Some properties and characterizations are given and a comparison with the previous sorts of approximation is obtained.
A.M. Kozae, H.M. Abu-Donia
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Granular Computing and Computational Complexity
2010Granular computing is to imitate humans multigranular computing strategy to problem solving in order to endow computers with the same capability. Its final goal is to reduce the computational complexity. To the end, based on the simplicity principle the problem at hand should be represented as simpler as possible.
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Granular representation and granular computing with fuzzy sets
Fuzzy Sets and Systems, 2012In this study, we introduce a concept of a granular representation of numeric membership functions of fuzzy sets, which offers a synthetic and qualitative view at fuzzy sets and their ensuing processing. The notion of consistency of the granular representation is formed, which helps regard the problem as a certain optimization task.
Adam Pedrycz +3 more
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Granular Computing and Human-Centricity in Computational Intelligence
9th IEEE International Conference on Cognitive Informatics (ICCI'10), 2010Information granules and ensuing Granular Computing offer interesting opportunities to endow processing with an important facet of human-centricity. This facet implies that the underlying processing supports non-numeric data inherently associated with the variable perception of humans. Systems that commonly become distributed and hierarchical, managing
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Approximation Spaces in Rough–Granular Computing
Fundamenta Informaticae, 2010We discuss some generalizations of the approximation space definition introduced in 1994 [24, 25]. These generalizations are motivated by real-life applications. Rough set based strategies for extension of such generalized approximation spaces from samples of objects onto their extensions are discussed.
Skowron, Andrzej +2 more
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Concept Granular Computing Systems
2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009Object-oriented and property-oriented concept lattices are constructed based on rough set theory. In this paper, a uniform mathematical model-concept granular computing system is first established by mappings on two complete lattices. In this framework, object-oriented and property-oriented concept granular computing systems are introduced for property-
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Advances in Granular Computing
2016This book is a research compendium in the area of Fuzzy Granular Computing. Two main branches are handled, a proposed fuzzy granulating algorithm, and higher-type information granuleHigher-type information granule formation, although more work was performed on the latter.
Mauricio A. Sanchez +2 more
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2011
Computational linguistics is a sub-field of artificial intelligence; it is an interdisciplinary field dealing with statistical and/or rule-based modeling of natural language from a computational perspective. Traditionally, fuzzy logic is used to deal with fuzziness among single linguistic terms in documents.
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Computational linguistics is a sub-field of artificial intelligence; it is an interdisciplinary field dealing with statistical and/or rule-based modeling of natural language from a computational perspective. Traditionally, fuzzy logic is used to deal with fuzziness among single linguistic terms in documents.
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