A spectral approach to clustering numerical vectors as nodes in a network
type: Item
instance of: scholarly article
title: A spectral approach to clustering numerical vectors as nodes in a network
zbMATH Open document ID: 1211.68363
author: Motoki Shiga
author: Ichigaku Takigawa
author: Hiroshi Mamitsuka
published in: Pattern Recognition
publication date: 2010-12-23T00:00:00Z
Mathematics Subject Classification ID: 68T10
zbMATH DE Number: 5829382
zbMATH Keywords: semi-supervised clustering
zbMATH Keywords: heterogeneous data
zbMATH Keywords: data integration
zbMATH Keywords: spectral clustering
describes a project that uses: Graclus
MaRDI profile type: Publication
full work available at URL: j.patcog.2010.08.010
OpenAlex ID: W1995120512
Wikidata QID: Q62669629
cites work: A survey of kernel and spectral methods for clustering
cites work: Semi-supervised graph clustering: a kernel approach
cites work: A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
cites work: Soft memberships for spectral clustering, with application to permeable language distinction
cites work: Concept decompositions for large sparse text data using clustering
cites work: Emergence of Scaling in Random Networks
cites work: 10.1162/1532443041827943
DOI: 10.1016/J.PATCOG.2010.08.010
DBLP publication ID: journals/pr/ShigaTM11
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description: scientific article; zbMATH DE number 5829382