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
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;
Conference_Titel :
Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8041-8
DOI :
10.1109/COGINF.2010.5599784
