Data Structure and Algorithm in Data Mining: Granular Computing View

Author

Tsumoto, Shusaku

Author_Institution

Dept. of Med. Informatics, Shimane Univ., Izumo

Volume

1

fYear

2006

fDate

17-21 Sept. 2006

Firstpage

26

Lastpage

27

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

Keywords

data mining; data structures; divide and conquer methods; knowledge based systems; pattern classification; data mining; data partition; data structure; divide and conquer; granular computing; information granules; rule mining; table structure; Application software; Biomedical informatics; Computer applications; Data mining; Data structures; Lab-on-a-chip; Network address translation; Psychology; Rough sets;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Software and Applications Conference, 2006. COMPSAC '06. 30th Annual International

Conference_Location

Chicago, IL

ISSN

0730-3157

Print_ISBN

0-7695-2655-1

Type

conf

DOI

10.1109/COMPSAC.2006.37

Filename

4020048