Data Structure and Algorithm in Data Mining: Granular Computing View
2 Citations•2006•
S. Tsumoto
journal unavailable
It is illustrated that granular computing gives a unified view of these two approaches of conventional style of rule mining, which may lead to theoretical foundations of data mining in the near future.
Abstract
This paper discusses foundations of conventional style of rule mining in which rules are extracted from a data table. Rule mining mainly uses the structure of a table, data partition, but two different approaches are observed: divide and conquer and covering: the former focuses on the nature of data partition and the latter does on the nature of information granules. This paper illustrates that granular computing gives a unified view of these two approaches, which may lead to theoretical foundations of data mining in the near future.