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
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;
Conference_Titel :
Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International
Conference_Location :
London
Print_ISBN :
1-4244-1209-9
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2007.4295476
