DocumentCode
2541292
Title
Concept reduction on interval formal concept analysis
Author
Wen, Zhou ; Yan, Zhao ; Yao, Li ; Zhaoman, Zhong
Author_Institution
Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai, China
fYear
2010
fDate
7-9 July 2010
Firstpage
899
Lastpage
903
Abstract
A concept clustering method on interval concept lattice is introduced in this paper. Based on the distance between two formal concepts defined, the clustering method is presented. Clustering can reduce the size of interval concept lattice to get better interval lattice structure which can be easier to understand. Experimental results show that the reduction algorithm has reasonable performance on the complexity.
Keywords
computational complexity; data analysis; concept clustering method; concept reduction; data analysis technique; interval concept lattice; interval formal concept analysis; Barium; Clustering methods; Cognitive informatics; Conferences; Lattices; interval FCA; interval clustering; interval concept lattice; reduction of interval lattice;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-8041-8
Type
conf
DOI
10.1109/COGINF.2010.5599784
Filename
5599784
Link To Document