Abstract
Granular computing has impact on development methods in such areas as knowledge discovery and data mining. This paper firstly presents a new axiomatic definition of knowledge granularity, then gives a series of methods of measuring knowledge granularity including concrete measurements lacking parameters and general measurements with parameters. Furthermore, several combinatorial forms of different granularity formulas are described. The principal results seem to have some theoretic and applied value to build granularity computation in information system.
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Zhao, Mq., Yang, Q., Gao, Dz. (2008). Axiomatic Definition of Knowledge Granularity and Its Constructive Method. In: Wang, G., Li, T., Grzymala-Busse, J.W., Miao, D., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2008. Lecture Notes in Computer Science(), vol 5009. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79721-0_49
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DOI: https://doi.org/10.1007/978-3-540-79721-0_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79720-3
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