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  • × theme_ss:"Automatisches Indexieren"
  1. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.02 
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    Date
    20.10.2000 12:22:23
  2. 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
  3. Fuhr, N.; Knorz, G.: Retrieval test evaluation of a rule based automatic indexing (AIR/PHYS) (1984) 0.02 
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  4. Salton, G.: Future prospects for text-based information retrieval (1990) 0.02 
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  5. Salton, G.; Araya, J.: On the use of clustered file organizations in information search and retrieval (1990) 0.02 
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  6. Lustig, G.: Methoden der automatischen Indexierung (1970) 0.02 
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  7. 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
  8. Knorz, G.: Automatische Indexierung (1994) 0.02 
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  9. Biebricher, P.; Fuhr, N.; Knorz, G.; Lustig, G.; Schwandtner, M.: Entwicklung und Anwendung des automatischen Indexierungssystems AIR/PHYS (1988) 0.02 
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  10. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.02 
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    Date
    14. 6.2015 22:12:44
  11. 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
  12. Hauer, M.: Tiefenindexierung im Bibliothekskatalog : 17 Jahre intelligentCAPTURE (2019) 0.02 
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    Source
    B.I.T.online. 22(2019) H.2, S.163-166
  13. 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.
  14. Salton, G.: Another look at automatic text-retrieval systems (1986) 0.02 
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  15. Salton, G.; McGill, M. J.: Information Retrieval: Grundlegendes für Informationswissenschaftler (1987) 0.02 
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  16. Salton, G.: Automatic text processing : the transformation, analysis, and retrieval of information by computer (1989) 0.02 
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  17. Biebricher, P.; Fuhr, N.; Niewelt, B.: ¬Der AIR-Retrievaltest (1986) 0.02 
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    Source
    Automatische Indexierung zwischen Forschung und Anwendung, Hrsg.: G. Lustig
  18. Salton, G.; Wong, A.; Yang, C.S.: ¬A vector space model for automatic indexing (1975) 0.02 
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  19. Salton, G.; Allan, J.; Buckley, C.; Singhal, A.: Automatic analysis, theme generation, and summarization of machine readable texts (1994) 0.02 
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  20. McKiernan, G.: Automated categorisation of Web resources : a profile of selected projects, research, products, and services (1996) 0.02 
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