DocumentCode :
2851764
Title :
Relational peculiarity oriented data mining
Author :
Zhong, Ning ; Liu, Chunnian ; Yao, Y.Y. ; Ohshima, Muneaki ; Huang, Mingxin ; Huang, Jiajin
Author_Institution :
Dept. of Inf. Eng., Maebashi Inst. of Technol., Japan
fYear :
2004
fDate :
1-4 Nov. 2004
Firstpage :
575
Lastpage :
578
Abstract :
Peculiarity rules are a new type of interesting rules which can be discovered by searching the relevance among peculiar data. A main task of mining peculiarity rules is the identification of peculiarity. Traditional methods of finding peculiar data are attribute-based approaches. This paper extends peculiarity oriented mining to relational peculiarity oriented mining. Peculiar data are identified on record level, and peculiar rules are mined and explained in a relational mining framework. The results from preliminary experiments show that relational peculiarity oriented mining is very effective.
Keywords :
data mining; relational databases; attribute-based approach; peculiarity identification; peculiarity rules; relational peculiarity oriented data mining; Brain modeling; Computer science; Data engineering; Data mining; Educational institutions; Image databases; Laboratories; Learning systems; Logic programming; Relational databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, 2004. ICDM '04. Fourth IEEE International Conference on
Print_ISBN :
0-7695-2142-8
Type :
conf
DOI :
10.1109/ICDM.2004.10008
Filename :
1410364
Link To Document :
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