Hybrid fragment mining with MoFA and FSG

Lade...
Vorschaubild
Dateien
Hybrid_fragment_mining_with_MoFA_and_FSG.pdf
Hybrid_fragment_mining_with_MoFA_and_FSG.pdfGröße: 241.47 KBDownloads: 286
Datum
2004
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583). IEEE, 2004, pp. 4559-4564. ISBN 0-7803-8567-5. Available under: doi: 10.1109/ICSMC.2004.1401250
Zusammenfassung

In the last few years a number of different subgraph mining algorithms have been proposed. They are often used for finding frequent fragments in molecular databases. All these algorithms behave quite well when used on small datasets of not more than a few thousand molecules. However, they all fail on larger amounts of data because they are either time consuming or have enormous memory requirements. In this paper we present a hybrid mining technique that overcomes the individual problems of the underlying algorithms and outperforms the individual methods impressively on large databases.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Molecules, fragments, graph mining, hybrid algorithm
Konferenz
2004 IEEE International Conference on Systems, Man and Cybernetics, The Hague, Netherlands
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690MEINL, Thorsten, Michael R. BERTHOLD, 2004. Hybrid fragment mining with MoFA and FSG. 2004 IEEE International Conference on Systems, Man and Cybernetics. The Hague, Netherlands. In: 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583). IEEE, 2004, pp. 4559-4564. ISBN 0-7803-8567-5. Available under: doi: 10.1109/ICSMC.2004.1401250
BibTex
@inproceedings{Meinl2004Hybri-5541,
  year={2004},
  doi={10.1109/ICSMC.2004.1401250},
  title={Hybrid fragment mining with MoFA and FSG},
  isbn={0-7803-8567-5},
  publisher={IEEE},
  booktitle={2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)},
  pages={4559--4564},
  author={Meinl, Thorsten and Berthold, Michael R.}
}
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/123456789/5541">
    <dc:format>application/pdf</dc:format>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5541/1/Hybrid_fragment_mining_with_MoFA_and_FSG.pdf"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dcterms:issued>2004</dcterms:issued>
    <dc:language>eng</dc:language>
    <dc:contributor>Meinl, Thorsten</dc:contributor>
    <dcterms:bibliographicCitation>First publ. in: 2004 IEEE International Conference on Systems, Man &amp; Cybernetics, The Hague, Netherlands, 10 - 13 October 2004.  Piscataway, NJ : IEEE Operations Center, 2004, pp. 4559-4564</dcterms:bibliographicCitation>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:creator>Meinl, Thorsten</dc:creator>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5541/1/Hybrid_fragment_mining_with_MoFA_and_FSG.pdf"/>
    <dc:contributor>Berthold, Michael R.</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:56:18Z</dc:date>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by-nc-nd/2.0/"/>
    <dc:rights>Attribution-NonCommercial-NoDerivs 2.0 Generic</dc:rights>
    <dcterms:title>Hybrid fragment mining with MoFA and FSG</dcterms:title>
    <dc:creator>Berthold, Michael R.</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5541"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:56:18Z</dcterms:available>
    <dcterms:abstract xml:lang="eng">In the last few years a number of different subgraph mining algorithms have been proposed. They are often used for finding frequent fragments in molecular databases. All these algorithms behave quite well when used on small datasets of not more than a few thousand molecules. However, they all fail on larger amounts of data because they are either time consuming or have enormous memory requirements. In this paper we present a hybrid mining technique that overcomes the individual problems of the underlying algorithms and outperforms the individual methods impressively on large databases.</dcterms:abstract>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
Prüfdatum der URL
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Diese Publikation teilen