A spectral approach to clustering numerical vectors as nodes in a network

DOI10.1016/j.patcog.2010.08.010zbMath1211.68363OpenAlexW1995120512WikidataQ62669629 ScholiaQ62669629MaRDI QIDQ614073

Motoki Shiga, Hiroshi Mamitsuka, Ichigaku Takigawa

Publication date: 23 December 2010

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2010.08.010

zbMATH Keywords

data integrationspectral clusteringheterogeneous datasemi-supervised clustering

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (1)

Label propagation algorithm for community detection based on node importance and label influence

Uses Software

• Graclus

Cites Work

• Soft memberships for spectral clustering, with application to permeable language distinction
• Semi-supervised graph clustering: a kernel approach
• A survey of kernel and spectral methods for clustering
• Emergence of Scaling in Random Networks
• A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
• 10.1162/1532443041827943
• Concept decompositions for large sparse text data using clustering

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