Search (19 results, page 1 of 1)

  • × theme_ss:"Computerlinguistik"
  • × language_ss:"d"
  1. Bátori, I.: ¬Der sprachliche Verarbeitungsprozeß als paradigmatischer Kern der linguistischen Datenverarbeitung (1982) 0.05
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    Pages
    S.71-90
  2. 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
  3. ¬Der Student aus dem Computer (2023) 0.02
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    Date
    27. 1.2023 16:22:55
  4. 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
  5. 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
  6. 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
  7. Menge-Sonnentag, R.: Google veröffentlicht einen Parser für natürliche Sprache (2016) 0.02
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    Content
    SyntaxNet nutzt zur Entscheidung neuronale Netze und versucht die Abhängigkeiten richtig zuzuordnen. Damit "lernt" der Parser, dass es schwierig ist, Sonnenblumenkerne zum Schneiden einzusetzen, und sie somit wohl eher Bestandteil des Brots als ein Werkzeug sind. Die Analyse beschränkt sich jedoch auf den Satz selbst. Semantische Zusammenhänge berücksichtigt das Modell nicht. So lösen sich manche Mehrdeutigkeiten durch den Kontext auf: Wenn Alice im obigen Beispiel das Fernglas beim Verlassen des Hauses eingepackt hat, wird sie es vermutlich benutzen. Trefferquote Mensch vs. Maschine Laut dem Blog-Beitrag kommt Parsey McParseface auf eine Genauigkeit von gut 94 Prozent für Sätze aus dem Penn Treebank Project. Die menschliche Quote soll laut Linguisten bei 96 bis 97 Prozent liegen. Allerdings weist der Beitrag auch darauf hin, dass es sich bei den Testsätzen um wohlgeformte Texte handelt. Im Test mit Googles WebTreebank erreicht der Parser eine Genauigkeit von knapp 90 Prozent."
  8. Ruge, G.: Sprache und Computer : Wortbedeutung und Termassoziation. Methoden zur automatischen semantischen Klassifikation (1995) 0.01
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    Footnote
    Rez. in: Knowledge organization 22(1995) no.3/4, S.182-184 (M.T. Rolland)
  9. Lezius, W.: Morphy - Morphologie und Tagging für das Deutsche (2013) 0.01
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    Date
    22. 3.2015 9:30:24
  10. Bager, J.: ¬Die Text-KI ChatGPT schreibt Fachtexte, Prosa, Gedichte und Programmcode (2023) 0.01
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    Date
    29.12.2022 18:22:55
  11. Rieger, F.: Lügende Computer (2023) 0.01
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    Date
    16. 3.2023 19:22:55
  12. Schneider, R.: Web 3.0 ante portas? : Integration von Social Web und Semantic Web (2008) 0.01
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    Date
    22. 1.2011 10:38:28
  13. Lorenz, S.: Konzeption und prototypische Realisierung einer begriffsbasierten Texterschließung (2006) 0.01
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    Date
    22. 3.2015 9:17:30
  14. Sienel, J.; Weiss, M.; Laube, M.: Sprachtechnologien für die Informationsgesellschaft des 21. Jahrhunderts (2000) 0.01
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    Date
    26.12.2000 13:22:17
  15. Pinker, S.: Wörter und Regeln : Die Natur der Sprache (2000) 0.01
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    Date
    19. 7.2002 14:22:31
  16. Semantik, Lexikographie und Computeranwendungen : Workshop ... (Bonn) : 1995.01.27-28 (1996) 0.01
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    Date
    14. 4.2007 10:04:22
  17. Rötzer, F.: KI-Programm besser als Menschen im Verständnis natürlicher Sprache (2018) 0.01
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    Date
    22. 1.2018 11:32:44
  18. Schürmann, H.: Software scannt Radio- und Fernsehsendungen : Recherche in Nachrichtenarchiven erleichtert (2001) 0.01
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    Source
    Handelsblatt. Nr.79 vom 24.4.2001, S.22
  19. Melzer, C.: ¬Der Maschine anpassen : PC-Spracherkennung - Programme sind mittlerweile alltagsreif (2005) 0.01
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    Date
    3. 5.1997 8:44:22

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