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