DocumentCode :
2328746
Title :
The mining of classification rules based on multiple extended concept lattices
Author :
Hu, Xue-Gang ; Chen, Hui ; Ma, Feng
Author_Institution :
Sch. of Comput. & Inf., Hefei Univ. of Technol., China
Volume :
4
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
2063
Abstract :
Mining classification rules is an important research area in data mining. Distributed data mining is one of the important research fields. So inducing classification rules from multiple data sources and amalgamating rules become the hotspot. The extended concept lattice is the extending of Galois concept lattice, which is effective for mining classification rules. In this paper, mining classification rules based on multiple extended concept lattices is described, the method of amalgamating rules is discussed and proved by theory and experiment.
Keywords :
data mining; knowledge representation; Galois concept lattice; classification rule mining; data mining; multiple extended concept lattice; Cybernetics; Data mining; Electronic mail; Lattices; Machine learning; Supervised learning; Classification Rule; Data Mining; Extended Concept Lattice;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527285
Filename :
1527285
Link To Document :
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