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.