High Performance Subgraph Mining in Molecular Compounds

Di Fatta, Giuseppe; Berthold, Michael R.

High Performance Subgraph Mining in Molecular Compounds

Dateien

Fatta_240449.pdfGröße: 471.81 KBDownloads: 270

Datum

2005

Autor:innen

Di Fatta, Giuseppe

Berthold, Michael R.

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

YANG, Laurence T., ed., Omer F. RANA, ed., Beniamino DI MARTINO, ed., Jack DONGARRA, ed.. High Performance Computing and Communications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005, pp. 866-877. Lecture Notes in Computer Science. 3726. ISBN 978-3-540-29031-5. Available under: doi: 10.1007/11557654_97

Zusammenfassung

Structured data represented in the form of graphs arises in several fields of the science and the growing amount of available data makes distributed graph mining techniques particularly relevant. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiver-initiated, load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening dataset, where the approach attains close-to linear speedup in a network of workstations.

Fachgebiet (DDC)

004 Informatik

Zitieren

ISO 690

DI FATTA, Giuseppe, Michael R. BERTHOLD, 2005. High Performance Subgraph Mining in Molecular Compounds. In: YANG, Laurence T., ed., Omer F. RANA, ed., Beniamino DI MARTINO, ed., Jack DONGARRA, ed.. High Performance Computing and Communications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005, pp. 866-877. Lecture Notes in Computer Science. 3726. ISBN 978-3-540-29031-5. Available under: doi: 10.1007/11557654_97

BibTex

@inproceedings{DiFatta2005Perfo-24044,
  year={2005},
  doi={10.1007/11557654_97},
  title={High Performance Subgraph Mining in Molecular Compounds},
  number={3726},
  isbn={978-3-540-29031-5},
  publisher={Springer Berlin Heidelberg},
  address={Berlin, Heidelberg},
  series={Lecture Notes in Computer Science},
  booktitle={High Performance Computing and Communications},
  pages={866--877},
  editor={Yang, Laurence T. and Rana, Omer F. and Di Martino, Beniamino and Dongarra, Jack},
  author={Di Fatta, Giuseppe 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/123456789/24044">
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/24044/1/Fatta_240449.pdf"/>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/24044"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-07-25T09:56:43Z</dcterms:available>
    <dc:rights>terms-of-use</dc:rights>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Berthold, Michael R.</dc:contributor>
    <dcterms:bibliographicCitation>High performance computing and communications : First International Conference, HPCC 2005, Sorrento, Italy, September 21 - 23, 2005; proceedings / Laurence T. Yang ... (ed.). - Berlin [u.a.]: Springer, 2005. - S. 866-877. - (Lecture notes in computer science ; 3726). - ISBN 978-3-540-29031-5</dcterms:bibliographicCitation>
    <dc:creator>Di Fatta, Giuseppe</dc:creator>
    <dc:creator>Berthold, Michael R.</dc:creator>
    <dcterms:abstract xml:lang="eng">Structured data represented in the form of graphs arises in several fields of the science and the growing amount of available data makes distributed graph mining techniques particularly relevant. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiver-initiated, load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening dataset, where the approach attains close-to linear speedup in a network of workstations.</dcterms:abstract>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dcterms:title>High Performance Subgraph Mining in Molecular Compounds</dcterms:title>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-07-25T09:56:43Z</dc:date>
    <dc:contributor>Di Fatta, Giuseppe</dc:contributor>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:language>eng</dc:language>
    <dcterms:issued>2005</dcterms:issued>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/24044/1/Fatta_240449.pdf"/>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
  </rdf:Description>
</rdf:RDF>

Universitätsbibliographie

Ja