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Erschienen in:
2014 | OriginalPaper | Buchkapitel
A Fuzzy Semisupervised Clustering Method: Application to the Classification of Scientific Publications
verfasst von : Irene Diaz-Valenzuela, Maria J. Martin-Bautista, Maria-Amparo Vila
Erschienen in: Information Processing and Management of Uncertainty in Knowledge-Based Systems
Verlag: Springer International Publishing
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This paper introduces a new method of fuzzy semisupervised hierarchical clustering using fuzzy instance level constraints. It introduces the concepts of fuzzy must-link and fuzzy cannot-link constraints and use them to find the optimum
α
-cut of a dendrogram. This method is used to approach the problem of classifying scientific publications in web digital libraries. It is tested on real data from that problem against classical methods and crisp semisupervised hierarchical clustering.