DocumentCode
2248690
Title
Granular data model: semantic data mining and computing with words
Author
Lin, T.Y.
Author_Institution
Dept. of Comput. Sci., San Jose State Univ., CA, USA
Volume
2
fYear
2004
fDate
25-29 July 2004
Firstpage
1141
Abstract
Using computing with words as a representation theory of Lin-Zadeh´s notion of granular computing, the bitmap indexes of relational tables is formalized and extended. We call it a granular data model (GDM). If all granulations are partitions, a GDM is reduced to a classical relation in relational data model. Based on GDM, semantically rich rules can be mined. The underlying theme of this paper is computing with words; data mining on GDM is one form of computing with words.
Keywords
data mining; data models; knowledge representation; relational databases; word processing; bitmap indexes; granular computing; granular data model; relational data model; relational tables; representation theory; semantic data mining; word processing; Computer science; Data analysis; Data mining; Data models; Data processing; Knowledge representation; Mathematics; Relational databases; Set theory; Stress;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on
ISSN
1098-7584
Print_ISBN
0-7803-8353-2
Type
conf
DOI
10.1109/FUZZY.2004.1375572
Filename
1375572
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