Search (10 results, page 1 of 1)

  • × language_ss:"e"
  • × theme_ss:"Automatisches Klassifizieren"
  • × year_i:[1990 TO 2000}
  1. Koch, T.; Vizine-Goetz, D.: DDC and knowledge organization in the digital library : Research and development. Demonstration pages (1999) 0.01 
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    Abstract
    Der Workshop gibt einen Einblick in die aktuelle Forschung und Entwicklung zur Wissensorganisation in digitalen Bibliotheken. Diane Vizine-Goetz vom OCLC Office of Research in Dublin, Ohio, stellt die Forschungsprojekte von OCLC zur Anpassung und Weiterentwicklung der Dewey Decimal Classification als Wissensorganisationsinstrument fuer grosse digitale Dokumentensammlungen vor. Traugott Koch, NetLab, Universität Lund in Schweden, demonstriert die Ansätze und Lösungen des EU-Projekts DESIRE zum Einsatz von intellektueller und vor allem automatischer Klassifikation in Fachinformationsdiensten im Internet.
    Footnote
    Vortrag anläßlich des Workshops am 21.10.1999, Deutsche Bibliothek, Frankfurt/M.
  2. Chan, L.M.; Lin, X.; Zeng, M.: Structural and multilingual approaches to subject access on the Web (1999) 0.01 
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    Abstract
    Zu den großen Herausforderungen einer sinnvollen Suche im WWW gehören die riesige Menge des Verfügbaren und die Sparchbarrieren. Verfahren, die die Web-Ressourcen im Hinblick auf ein effizienteres Retrieval inhaltlich strukturieren, werden daher ebenso dringend benötigt wie Programme, die mit der Sprachvielfalt umgehen können. Im folgenden Vortrag werden wir einige Ansätze diskutieren, die zur Bewältigung der beiden Probleme derzeit unternommen werden
  3. Sebastiani, F.: ¬A tutorial an automated text categorisation (1999) 0.00 
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    Abstract
    The automated categorisation (or classification) of texts into topical categories has a long history, dating back at least to 1960. Until the late '80s, the dominant approach to the problem involved knowledge-engineering automatic categorisers, i.e. manually building a set of rules encoding expert knowledge an how to classify documents. In the '90s, with the booming production and availability of on-line documents, automated text categorisation has witnessed an increased and renewed interest. A newer paradigm based an machine learning has superseded the previous approach. Within this paradigm, a general inductive process automatically builds a classifier by "learning", from a set of previously classified documents, the characteristics of one or more categories; the advantages are a very good effectiveness, a considerable savings in terms of expert manpower, and domain independence. In this tutorial we look at the main approaches that have been taken towards automatic text categorisation within the general machine learning paradigm. Issues of document indexing, classifier construction, and classifier evaluation, will be touched upon.
  4. Vizine-Goetz, D.: NetLab / OCLC collaboration seeks to improve Web searching (1999) 0.00 
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    Abstract
    Vorstellung verschiedener Projekte zur Verbesserung der Internet-Erschließung mit Hilfe der DDC
  5. Savic, D.: Designing an expert system for classifying office documents (1994) 0.00 
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    Source
    Records management quarterly. 28(1994) no.3, S.20-29
  6. Savic, D.: Automatic classification of office documents : review of available methods and techniques (1995) 0.00 
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    Source
    Records management quarterly. 29(1995) no.4, S.3-18
  7. Ruocco, A.S.; Frieder, O.: Clustering and classification of large document bases in a parallel environment (1997) 0.00 
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    Date
    29. 7.1998 17:45:02
  8. Dubin, D.: Dimensions and discriminability (1998) 0.00 
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    Date
    22. 9.1997 19:16:05
  9. Jenkins, C.: Automatic classification of Web resources using Java and Dewey Decimal Classification (1998) 0.00 
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    Date
    1. 8.1996 22:08:06
  10. Ingwersen, P.; Wormell, I.: Ranganathan in the perspective of advanced information retrieval (1992) 0.00 
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