Publikation:

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: 306

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

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

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

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