Search (27 results, page 1 of 2)

  • × year_i:[2000 TO 2010}
  • × theme_ss:"Automatisches Indexieren"
  1. Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006) 0.05 
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    Date
    24. 3.2006 12:22:02
  2. Probst, M.; Mittelbach, J.: Maschinelle Indexierung in der Sacherschließung wissenschaftlicher Bibliotheken (2006) 0.05 
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    22. 3.2008 12:35:19
  3. Hlava, M.M.K.: Automatic indexing : comparing rule-based and statistics-based indexing systems (2005) 0.02 
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    Source
    Information outlook. 9(2005) no.8, S.22-23
  4. Hauer, M.: Automatische Indexierung (2000) 0.02 
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    Source
    Wissen in Aktion: Wege des Knowledge Managements. 22. Online-Tagung der DGI, Frankfurt am Main, 2.-4.5.2000. Proceedings. Hrsg.: R. Schmidt
  5. Oberhauser, O.; Labner, J.: Einführung der automatischen Indexierung im Österreichischen Verbundkatalog? : Bericht über eine empirische Studie (2003) 0.02 
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  6. Anderson, J.D.; Pérez-Carballo, J.: ¬The nature of indexing: how humans and machines analyze messages and texts for retrieval : Part I: Research and the nature of human indexing (2001) 0.02 
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  7. Thirion, B.; Leroy, J.P.; Baudic, F.; Douyère, M.; Piot, J.; Darmoni, S.J.: SDI selecting, decribing, and indexing : did you mean automatically? (2001) 0.02 
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  8. Rapke, K.: Automatische Indexierung von Volltexten für die Gruner+Jahr Pressedatenbank (2001) 0.02 
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    Abstract
    Retrieval Tests sind die anerkannteste Methode, um neue Verfahren der Inhaltserschließung gegenüber traditionellen Verfahren zu rechtfertigen. Im Rahmen einer Diplomarbeit wurden zwei grundsätzlich unterschiedliche Systeme der automatischen inhaltlichen Erschließung anhand der Pressedatenbank des Verlagshauses Gruner + Jahr (G+J) getestet und evaluiert. Untersucht wurde dabei natürlichsprachliches Retrieval im Vergleich zu Booleschem Retrieval. Bei den beiden Systemen handelt es sich zum einen um Autonomy von Autonomy Inc. und DocCat, das von IBM an die Datenbankstruktur der G+J Pressedatenbank angepasst wurde. Ersteres ist ein auf natürlichsprachlichem Retrieval basierendes, probabilistisches System. DocCat demgegenüber basiert auf Booleschem Retrieval und ist ein lernendes System, das auf Grund einer intellektuell erstellten Trainingsvorlage indexiert. Methodisch geht die Evaluation vom realen Anwendungskontext der Textdokumentation von G+J aus. Die Tests werden sowohl unter statistischen wie auch qualitativen Gesichtspunkten bewertet. Ein Ergebnis der Tests ist, dass DocCat einige Mängel gegenüber der intellektuellen Inhaltserschließung aufweist, die noch behoben werden müssen, während das natürlichsprachliche Retrieval von Autonomy in diesem Rahmen und für die speziellen Anforderungen der G+J Textdokumentation so nicht einsetzbar ist
  9. Maas, J.: Anforderungsanalyse für den Einsatz eines (semi)automatischen Indexierungsverfahrens in der Textdokumentation des ZDF (2002) 0.02 
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  10. Gaese, V.: "Automatische Klassifikation von Presseartikeln in der Gruner + Jahr Dokumentation" (2003) 0.01 
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    Abstract
    Das Klassifizieren von Texten, auch Indexieren, inhaltliches Erschließen oder verschlagworten genannt, gehört seit jeher zu den zwar notwendigen aber sehr aufwändigen Aufgaben von Archiven bzw. Dokumentationen. Ihre unterschiedlichen Zwecke bzw. Anforderungen sind sicher ein Grund dafür, dass es fast ebenso viele Erschließungsinventare, Thesauri oder Schlagwortverzeichnisse wie Dokumentationen gibt. Im folgenden werden Klassifizierung, Indexierung, Erschließung und Verschlagwortung synonym verwendet. In der G+J Dokumentation arbeiten heute ca. 20 Dokumentare an Auswahl und Erschließung von täglich etwa 1.100 Artikeln aus insgesamt ca. 210 Titeln. In der G+J Pressedatenbank sind aktuell ca. 7 Mio Artikel gespeichert, gut 2 Mio als digitaler Volltext (OCR/Satzdaten). Archiviert sind nur Artikel, für die die G+J Dokumentation die entsprechenden Rechte hat.
  11. Rapke, K.: Automatische Indexierung von Volltexten für die Gruner+Jahr Pressedatenbank (2001) 0.01 
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    Abstract
    Retrievaltests sind die anerkannteste Methode, um neue Verfahren der Inhaltserschließung gegenüber traditionellen Verfahren zu rechtfertigen. Im Rahmen einer Diplomarbeit wurden zwei grundsätzlich unterschiedliche Systeme der automatischen inhaltlichen Erschließung anhand der Pressedatenbank des Verlagshauses Gruner + Jahr (G+J) getestet und evaluiert. Untersucht wurde dabei natürlichsprachliches Retrieval im Vergleich zu Booleschem Retrieval. Bei den beiden Systemen handelt es sich zum einen um Autonomy von Autonomy Inc. und DocCat, das von IBM an die Datenbankstruktur der G+J Pressedatenbank angepasst wurde. Ersteres ist ein auf natürlichsprachlichem Retrieval basierendes, probabilistisches System. DocCat demgegenüber basiert auf Booleschem Retrieval und ist ein lernendes System, das aufgrund einer intellektuell erstellten Trainingsvorlage indexiert. Methodisch geht die Evaluation vom realen Anwendungskontext der Textdokumentation von G+J aus. Die Tests werden sowohl unter statistischen wie auch qualitativen Gesichtspunkten bewertet. Ein Ergebnis der Tests ist, dass DocCat einige Mängel gegenüber der intellektuellen Inhaltserschließung aufweist, die noch behoben werden müssen, während das natürlichsprachliche Retrieval von Autonomy in diesem Rahmen und für die speziellen Anforderungen der G+J Textdokumentation so nicht einsetzbar ist
  12. Anderson, J.D.; Pérez-Carballo, J.: ¬The nature of indexing: how humans and machines analyze messages and texts for retrieval : Part II: Machine indexing, and the allocation of human versus machine effort (2001) 0.01 
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  13. Peters, G.: Verschlagwortung und automatische Verfahren in der G+J Dokumentation (2003) 0.01 
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  14. Renz, M.: Automatische Inhaltserschließung im Zeichen von Wissensmanagement (2001) 0.01 
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    Date
    22. 3.2001 13:14:48
  15. Newman, D.J.; Block, S.: Probabilistic topic decomposition of an eighteenth-century American newspaper (2006) 0.01 
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    Date
    22. 7.2006 17:32:00
  16. Lorenz, S.: Konzeption und prototypische Realisierung einer begriffsbasierten Texterschließung (2006) 0.01 
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    Date
    22. 3.2015 9:17:30
  17. Dolamic, L.; Savoy, J.: When stopword lists make the difference (2009) 0.01 
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  18. Goller, C.; Löning, J.; Will, T.; Wolff, W.: Automatic document classification : a thourough evaluation of various methods (2000) 0.01 
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  19. Oberhauser, O.; Labner, J.: OPAC-Erweiterung durch automatische Indexierung : Empirische Untersuchung mit Daten aus dem Österreichischen Verbundkatalog (2002) 0.01 
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  20. Mongin, L.; Fu, Y.Y.; Mostafa, J.: Open Archives data Service prototype and automated subject indexing using D-Lib archive content as a testbed (2003) 0.01 
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Authors

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  • d 14
  • e 13

Types

  • a 21
  • x 3
  • el 2
  • m 1
  • p 1
  • More… Less…

Themes