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Interpreting fuzzy clustering results based on Fuzzy Formal Concept Analysis
Conference proceeding

Interpreting fuzzy clustering results based on Fuzzy Formal Concept Analysis

Minyar Sassi Hidri, A. Grissa, H. Ounelli and IEEE
2007 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-4, p.846
IEEE International Conference on Fuzzy Systems
01/01/2007

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Theory & Methods Engineering Engineering, Electrical & Electronic Science & Technology Technology
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.

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