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ASME Press Select Proceedings
International Conference on Electronics, Information and Communication Engineering (EICE 2012)
Garry Lee
Garry Lee
Information Engineering Research Institute
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ASME Press
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Cloud theory is a new theory handling uncertainty based on the uncertain transition between quality and quantity. The theory includes cloud model, virtual cloud, cloud operation, cloud transform and uncertainty reasoning. It provides new solutions for many basic problems in data mining and knowledge discovery, such as concept and knowledge representation, transition between quality and quantity, concept synthesization and resolution, concept and concept hierarchy generation from data, etc. Clod model is a model of the uncertain transition between a linguistic term of a qualitative concept and its numerical representation. Cloud model represents a qualitative concept with three digital characteristics, expected value, entropy and hyper entropy, which integrate the fuzziness and randomness of a linguistic term in a unified way. This paper presents the fundamentals of cloud theory and its applications in spatial data mining and knowledge discovery, focusing on the cloud models and their algorithms.

Cloud Model
The Application of Cloud Theory in Spatial SDMKD
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