A Novel Semi-supervised Clustering Algorithm for Finding Clusters of Arbitrary Shapes

DOI10.1007/978-3-540-89985-3_123zbMath1188.68244OpenAlexW1624170038MaRDI QIDQ3628555

Saeed Bagheri Shouraki, Mahdieh Soleymani Baghshah

Publication date: 20 May 2009

Published in: Communications in Computer and Information Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-89985-3_123

zbMATH Keywords

clusteringsemi-supervisedpair wise constraintssub-clusters

Mathematics Subject Classification ID

Nonnumerical algorithms (68W05) Pattern recognition, speech recognition (68T10)

Related Items (1)

A Novel Semi-supervised Clustering Algorithm for Finding Clusters of Arbitrary Shapes

Cites Work

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• Correlation clustering
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• A Novel Semi-supervised Clustering Algorithm for Finding Clusters of Arbitrary Shapes
• Mixture Modeling with Pairwise, Instance-Level Class Constraints

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