Publikation:

Clustering on the net : applying autoassociative neural network to computer mediated discussions

Vorschaubild

Dateien

Zu diesem Dokument gibt es keine Dateien.

Datum

2006

Autor:innen

Sudweeks, Fay
Newton, Sid
Coyne, Richard

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

URI (zitierfähiger Link)
http://nbn-resolving.de/urn:nbn:de:bsz:352-242090
DOI (zitierfähiger Link)
https://doi.org/10.1111/j.1083-6101.1997.tb00202.x
ArXiv-ID

Internationale Patentnummer

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung

Sammlungen

Informatik und Informationswissenschaft: Publikationen
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen in

Journal of Computer-Mediated Communication. 2006, 2(4). ISSN 1083-6101. Available under: doi: 10.1111/j.1083-6101.1997.tb00202.x

Zusammenfassung

ProjectH, a research group of a hundred researchers, produced a huge amount of data from computer mediated discussions. The data classified several thousand postings from over 30 newsgroups into 46 categories. One approach to extract typical examples from this database is presented in this paper. An autoassociative neural network is trained on all 3000 coded messages and then used to construct typical messages under certain specified conditions. With this method the neural network can be used to create “typical” messages for several scenarios. This paper illustrates the architecture of the neural network that was used and explains the necessary modifications to the coding scheme. In addition several “typicality sets” produced by the neural net are shown and their generation is explained. In conclusion, the autoassociative neural network is used to explore threads and the types of messages that typically initiate or contribute longer lasting threads.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690BERTHOLD, Michael R., Fay SUDWEEKS, Sid NEWTON, Richard COYNE, 2006. Clustering on the net : applying autoassociative neural network to computer mediated discussions. In: Journal of Computer-Mediated Communication. 2006, 2(4). ISSN 1083-6101. Available under: doi: 10.1111/j.1083-6101.1997.tb00202.x
BibTex
@article{Berthold2006Clust-24209,
  year={2006},
  doi={10.1111/j.1083-6101.1997.tb00202.x},
  title={Clustering on the net : applying autoassociative neural network to computer mediated discussions},
  number={4},
  volume={2},
  issn={1083-6101},
  journal={Journal of Computer-Mediated Communication},
  author={Berthold, Michael R. and Sudweeks, Fay and Newton, Sid and Coyne, Richard}
}
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/123456789/24209">
    <dc:contributor>Newton, Sid</dc:contributor>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/24209"/>
    <dcterms:abstract xml:lang="eng">ProjectH, a research group of a hundred researchers, produced a huge amount of data from computer mediated discussions. The data classified several thousand postings from over 30 newsgroups into 46 categories. One approach to extract typical examples from this database is presented in this paper. An autoassociative neural network is trained on all 3000 coded messages and then used to construct typical messages under certain specified conditions. With this method the neural network can be used to create “typical” messages for several scenarios. This paper illustrates the architecture of the neural network that was used and explains the necessary modifications to the coding scheme. In addition several “typicality sets” produced by the neural net are shown and their generation is explained. In conclusion, the autoassociative neural network is used to explore threads and the types of messages that typically initiate or contribute longer lasting threads.</dcterms:abstract>
    <dc:creator>Coyne, Richard</dc:creator>
    <dc:contributor>Sudweeks, Fay</dc:contributor>
    <dc:contributor>Coyne, Richard</dc:contributor>
    <dcterms:issued>2006</dcterms:issued>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:creator>Berthold, Michael R.</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-08-23T13:56:59Z</dcterms:available>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Berthold, Michael R.</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-08-23T13:56:59Z</dc:date>
    <dcterms:title>Clustering on the net : applying autoassociative neural network to computer mediated discussions</dcterms:title>
    <dc:creator>Sudweeks, Fay</dc:creator>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:bibliographicCitation>Journal of Computer-Mediated Communication ; 2 (1997), 4.</dcterms:bibliographicCitation>
    <dc:language>eng</dc:language>
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Newton, Sid</dc:creator>
  </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