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  • × theme_ss:"Computerlinguistik"
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  1. Ohly, H.P.; Binder, G.: Semantisches Retrieval mit sozialwissenschaftlichen Dokumenten : erste Erfahrungen mit RELATIO/IR (1994) 0.02 
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  2. Sonnenberger, G.: Automatische Wissensakquisition aus Texten : Textparsing (1990) 0.02 
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  3. Schwarz, C.; Thurmair, G.: REALIST: eine Retrievalhilfe mit informationslinguistischen Komponenten (1986) 0.02 
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  4. Gachot, D.A.; Lange, E.; Yang, J.: ¬The SYSTRAN NLP browser : an application of machine translation technology in cross-language information retrieval (1998) 0.02 
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    Source
    Cross-language information retrieval. Ed.: G. Grefenstette
  5. Hull, D.; Ait-Mokhtar, S.; Chuat, M.; Eisele, A.; Gaussier, E.; Grefenstette, G.; Isabelle, P.; Samulesson, C.; Segand, F.: Language technologies and patent search and classification (2001) 0.02 
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  6. 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
  7. Vossen, P.; Bloksma, L.; Alonge, A.; Marinai, E.; Peters, C.; Catellon, I.; Marti, M.A.; Rigau, G.: Compatibility in interpretation of relations in EuroWordNet (1998) 0.02 
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  8. Peters, W.; Vossen, P.; Diez-Orzas, P.; Adriaens, G.: Cross-linguistic alignment of WordNets with an inter-lingual-index (1998) 0.02 
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  9. Bordogna, G.; Pasi, G.: ¬A fuzzy linguistic approach generalizing Boolean information retrieval : a model and its evaluation (1993) 0.02 
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  10. Byrne, C.C.; McCracken, S.A.: ¬An adaptive thesaurus employing semantic distance, relational inheritance and nominal compound interpretation for linguistic support of information retrieval (1999) 0.02 
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    Date
    15. 3.2000 10:22:37
  11. Monnerjahn, P.: Vorsprung ohne Technik : Übersetzen: Computer und Qualität (2000) 0.02 
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    Source
    c't. 2000, H.22, S.230-231
  12. Ruge, G.; Schwarz, C.: Term association and computational linguistics (1991) 0.02 
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  13. Satta, G.; Stock, O.: Bidirectional context-free grammar parsing for natural language processing (1994) 0.02 
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  14. Rapke, K.: Automatische Indexierung von Volltexten für die Gruner+Jahr Pressedatenbank (2001) 0.02 
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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
  15. Rahmstorf, G.: Wortmodell und Begriffssprache als Basis des semantischen Retrievals (2000) 0.02 
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    Source
    Informationskompetenz - Basiskompetenz in der Informationsgesellschaft: Proceedings des 7. Internationalen Symposiums für Informationswissenschaft (ISI 2000), Hrsg.: G. Knorz u. R. Kuhlen
  16. Hutchins, J.: From first conception to first demonstration : the nascent years of machine translation, 1947-1954. A chronology (1997) 0.02 
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    Date
    31. 7.1996 9:22:19
  17. Kuhlmann, U.; Monnerjahn, P.: Sprache auf Knopfdruck : Sieben automatische Übersetzungsprogramme im Test (2000) 0.02 
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    Source
    c't. 2000, H.22, S.220-229
  18. Lezius, W.; Rapp, R.; Wettler, M.: ¬A morphology-system and part-of-speech tagger for German (1996) 0.02 
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    Date
    22. 3.2015 9:37:18
  19. Rahmstorf, G.: Rückkehr von Ordnung in die Informationstechnik? (2000) 0.02 
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    Source
    Information und Öffentlichkeit: 1. Gemeinsamer Kongress der Bundesvereinigung Deutscher Bibliotheksverbände e.V. (BDB) und der Deutschen Gesellschaft für Informationswissenschaft und Informationspraxis e.V. (DGI), Leipzig, 20.-23.3.2000. Zugleich 90. Deutscher Bibliothekartag, 52. Jahrestagung der Deutschen Gesellschaft für Informationswissenschaft und Informationspraxis e.V. (DGI). Hrsg.: G. Ruppelt u. H. Neißer
  20. Ruge, G.: Experiments on linguistically-based term associations (1992) 0.01 
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