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  • × theme_ss:"Automatisches Indexieren"
  • × language_ss:"d"
  1. Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006) 0.03
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    Date
    24. 3.2006 12:22:02
  2. Probst, M.; Mittelbach, J.: Maschinelle Indexierung in der Sacherschließung wissenschaftlicher Bibliotheken (2006) 0.03
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    Date
    22. 3.2008 12:35:19
  3. Lepsky, K.: Vom OPAC zum Hyperkatalog : Daten und Indexierung (1996) 0.02
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    Source
    Erschließen, Suchen, Finden: Vorträge aus den bibliothekarischen Arbeitsgruppen der 19. und 20. Jahrestagungen (Basel 1995 / Freiburg 1996) der Gesellschaft für Klassifikation. Hrsg.: H.-J. Hermes u. H.-J. Wätjen
  4. Panyr, J.: STEINADLER: ein Verfahren zur automatischen Deskribierung und zur automatischen thematischen Klassifikation (1978) 0.02
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  5. Inhaltserschließung von Massendaten : zur Wirksamkeit informationslinguistischer Verfahren am Beispiel des deutschen Patentinformationssystems (1987) 0.02
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    Editor
    Krause, J.
  6. Oberhauser, O.; Labner, J.: Einführung der automatischen Indexierung im Österreichischen Verbundkatalog? : Bericht über eine empirische Studie (2003) 0.02
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  7. Gräbnitz, V.: PASSAT: Programm zur automatischen Selektion von Stichwörtern aus Texten (1987) 0.02
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    Source
    Inhaltserschließung von Massendaten zur Wirksamkeit informationslinguistischer Verfahren am Beispiel des Deutschen Patentinformationssystems. Hrsg. J. Krause
  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) 0.02
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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. Salton, G.; McGill, M. J.: Information Retrieval: Grundlegendes für Informationswissenschaftler (1987) 0.01
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  12. 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
  13. Peters, G.: Verschlagwortung und automatische Verfahren in der G+J Dokumentation (2003) 0.01
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