DocumentCode
3317444
Title
Interpreting Fuzzy Clustering Results based on Fuzzy Formal Concept Analysis
Author
Sassi, M. ; Grissa, A. ; Ounelli, Habib
Author_Institution
Nat. Sch. of Eng. of Tunis, Tunis
fYear
2007
fDate
23-26 July 2007
Firstpage
1
Lastpage
6
Abstract
The purpose of this paper is to construct structural information from the original data, where the results of fuzzy clustering can be displayed and interpreted. We use fuzzy formal concept analysis (FFCA) based technique for visual data mining and fuzzy clustering results interpretation. The visual interpretation and the navigation in the fuzzy lattice provided useful insights about the overlapping of different clusters and their relationships.
Keywords
data mining; fuzzy set theory; pattern clustering; fuzzy clustering; fuzzy formal concept analysis; fuzzy lattice; structural information; visual data mining; Clustering algorithms; Clustering methods; Data analysis; Data mining; Fuzzy logic; Fuzzy sets; Information analysis; Lattices; Navigation; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International
Conference_Location
London
ISSN
1098-7584
Print_ISBN
1-4244-1209-9
Electronic_ISBN
1098-7584
Type
conf
DOI
10.1109/FUZZY.2007.4295476
Filename
4295476
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