Clustering with Spectral Methods
Clustering with Spectral Methods
Loading...
Files
Date
2002
Authors
Gaertler, Marco
Editors
Journal ISSN
Electronic ISSN
ISBN
Bibliographical data
Publisher
Series
URI (citable link)
International patent number
Link to the license
EU project number
Project
Open Access publication
Collections
Title in another language
Publication type
Diploma thesis
Publication status
Published in
Abstract
Grouping and sorting are problems with a great tradition in the history of mankind. Clustering and cluster analysis is a small aspect in the wide spectrum. But these topics have applications in most scientific disciplines. Graph clustering is again a little fragment in the clustering area. Nevertheless it has the potential for new pioneering and innovative methods. One such method is the Markov Clustering presented by van Dongen in 'Graph Clustering by Flow Simulation'. We investigated the question, if there is a similar approach which involves the graph structure more directly and has a linear space complexity.
Summary in another language
Subject (DDC)
510 Mathematics
Keywords
Graphen-Clusterung,spektrale Einbettungen,Minimal-Spann-Bäume,Graph clustering,spectral methods and embeddings,minimum spanning trees
Conference
Review
undefined / . - undefined, undefined. - (undefined; undefined)
Cite This
ISO 690
GAERTLER, Marco, 2002. Clustering with Spectral Methods [Master thesis]BibTex
@mastersthesis{Gaertler2002Clust-717,
year={2002},
title={Clustering with Spectral Methods},
author={Gaertler, Marco}
}
RDF
<rdf:RDF
xmlns:dcterms="http://purl.org/dc/terms/"
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:bibo="http://purl.org/ontology/bibo/"
xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:void="http://rdfs.org/ns/void#"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#" >
<rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/717">
<dcterms:issued>2002</dcterms:issued>
<dc:language>eng</dc:language>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/717/1/thesis.pdf"/>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/>
<dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
<dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/717/1/thesis.pdf"/>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/>
<dc:contributor>Gaertler, Marco</dc:contributor>
<bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/717"/>
<dc:format>application/pdf</dc:format>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-22T17:45:36Z</dc:date>
<dc:creator>Gaertler, Marco</dc:creator>
<dcterms:title>Clustering with Spectral Methods</dcterms:title>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-22T17:45:36Z</dcterms:available>
<dcterms:abstract xml:lang="eng">Grouping and sorting are problems with a great tradition in the history of mankind. Clustering and cluster analysis is a small aspect in the wide spectrum. But these topics have applications in most scientific disciplines. Graph clustering is again a little fragment in the clustering area. Nevertheless it has the potential for new pioneering and innovative methods. One such method is the Markov Clustering presented by van Dongen in 'Graph Clustering by Flow Simulation'. We investigated the question, if there is a similar approach which involves the graph structure more directly and has a linear space complexity.</dcterms:abstract>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dc:rights>terms-of-use</dc:rights>
</rdf:Description>
</rdf:RDF>