云理论及其在空间数据发掘和知识发现中的应用

云理论是以研究定性定量间的不生转换为基础的系统处理不确定性问题的一新理论，包括云模型，虚云，云运算，云变换，不确定性推理等内容，云理论为数据发掘和知识发现中的许多基础性关键问题提供了新的解决方法，如概念和知识表达，定性定量转换，概念的综合与分解，从数据中生成概念和概念层次结构等。

Cloud Theory and Its Applications in Spatial Data Mining and Knowledge Discovery

Cloud theory is a new theory handling uncertainty based on the uncertain transition between qualitatives and quantitatives. 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 qualitatives and quantitatives, concept synthesization and resolution, concept and concept hierarchy generation from data, etc. Cloud 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 Ex , entropy En and hyper entropy He , 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.