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Data Structure and Algorithm in Data Mining: Granular Computing View
Chicago, Illinois September 17-September 21
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/COMPSAC.2006.3730th Annual International Computer So ...
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Shusaku Tsumoto, Shimane University, Japan
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.
Citation:
Shusaku Tsumoto, "Data Structure and Algorithm in Data Mining: Granular Computing View," compsac, vol. 1, pp.26-27, 30th Annual International Computer Software and Applications Conference (COMPSAC'06), 2006
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