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IJIT
2004

Fuzzy Clustering of Categorical Attributes and its Use in Analyzing Cultural Data

11 years 2 months ago
Fuzzy Clustering of Categorical Attributes and its Use in Analyzing Cultural Data
We develop a three-step fuzzy logic-based algorithm for clustering categorical attributes, and we apply it to analyze cultural data. In the first step the algorithm employs an entropy-based clustering scheme, which initializes the cluster centers. In the second step we apply the fuzzy c-modes algorithm to obtain a fuzzy partition of the data set, and the third step introduces a novel cluster validity index, which decides the final number of clusters. Keywords--Categorical data, cultural data, fuzzy logic clustering, fuzzy c-modes, cluster validity index.
George E. Tsekouras, Dimitris Papageorgiou, Sotiri
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where IJIT
Authors George E. Tsekouras, Dimitris Papageorgiou, Sotiris B. Kotsiantis, Christos Kalloniatis, Panayiotis E. Pintelas
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