Search (173 results, page 2 of 9)

  • × theme_ss:"Computerlinguistik"
  1. Chen, K.-H.: Evaluating Chinese text retrieval with multilingual queries (2002) 0.00 
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    Date
    6. 1.1997 18:30:28
    Source
    Knowledge organization. 29(2002) nos.3/4, S.156-170
  2. Bowker, L.: Information retrieval in translation memory systems : assessment of current limitations and possibilities for future development (2002) 0.00 
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    Date
    6. 1.1997 18:30:28
    Source
    Knowledge organization. 29(2002) nos.3/4, S.198-203
  3. Rindflesch, T.C.; Aronson, A.R.: Semantic processing in information retrieval (1993) 0.00 
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    Date
    29. 6.2015 14:51:28
  4. Schneider, R.: Web 3.0 ante portas? : Integration von Social Web und Semantic Web (2008) 0.00 
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    Date
    22. 1.2011 10:38:28
  5. Melby, A.: Some notes on 'The proper place of men and machines in language translation' (1997) 0.00 
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    Date
    31. 7.1996 9:22:19
    Source
    Machine translation. 12(1997) nos.1/2, S.29-34
  6. Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002) 0.00 
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    Date
    6. 1.1997 18:30:28
    Source
    Knowledge organization. 29(2002) nos.3/4, S.135-155
  7. Sidhom, S.; Hassoun, M.: Morpho-syntactic parsing for a text mining environment : An NP recognition model for knowledge visualization and information retrieval (2002) 0.00 
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    Date
    6. 1.1997 18:30:28
    Source
    Knowledge organization. 29(2002) nos.3/4, S.171-180
  8. L'Homme, D.; L'Homme, M.-C.; Lemay, C.: Benchmarking the performance of two Part-of-Speech (POS) taggers for terminological purposes (2002) 0.00 
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    Date
    6. 1.1997 18:30:28
    Source
    Knowledge organization. 29(2002) nos.3/4, S.204-216
  9. Albrecht, I.: GPT-3: die Zukunft studentischer Hausarbeiten oder eine Bedrohung der wissenschaftlichen Integrität? (2023) 0.00 
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    Date
    28. 1.2022 11:05:29
  10. Rötzer, F.: Computer ergooglen die Bedeutung von Worten (2005) 0.00 
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    Content
    "Wie könnten Computer Sprache lernen und dabei auch die Bedeutung von Worten sowie die Beziehungen zwischen ihnen verstehen? Dieses Problem der Semantik stellt eine gewaltige, bislang nur ansatzweise bewältigte Aufgabe dar, da Worte und Wortverbindungen oft mehrere oder auch viele Bedeutungen haben, die zudem vom außersprachlichen Kontext abhängen. Die beiden holländischen (Ein künstliches Bewusstsein aus einfachen Aussagen (1)). Paul Vitanyi (2) und Rudi Cilibrasi vom Nationalen Institut für Mathematik und Informatik (3) in Amsterdam schlagen eine elegante Lösung vor: zum Nachschlagen im Internet, der größten Datenbank, die es gibt, wird einfach Google benutzt. Objekte wie eine Maus können mit ihren Namen "Maus" benannt werden, die Bedeutung allgemeiner Begriffe muss aus ihrem Kontext gelernt werden. Ein semantisches Web zur Repräsentation von Wissen besteht aus den möglichen Verbindungen, die Objekte und ihre Namen eingehen können. Natürlich können in der Wirklichkeit neue Namen, aber auch neue Bedeutungen und damit neue Verknüpfungen geschaffen werden. Sprache ist lebendig und flexibel. Um einer Künstlichen Intelligenz alle Wortbedeutungen beizubringen, müsste mit der Hilfe von menschlichen Experten oder auch vielen Mitarbeitern eine riesige Datenbank mit den möglichen semantischen Netzen aufgebaut und dazu noch ständig aktualisiert werden. Das aber müsste gar nicht notwendig sein, denn mit dem Web gibt es nicht nur die größte und weitgehend kostenlos benutzbare semantische Datenbank, sie wird auch ständig von zahllosen Internetnutzern aktualisiert. Zudem gibt es Suchmaschinen wie Google, die Verbindungen zwischen Worten und damit deren Bedeutungskontext in der Praxis in ihrer Wahrscheinlichkeit quantitativ mit der Angabe der Webseiten, auf denen sie gefunden wurden, messen.
  11. Ibekwe-SanJuan, F.; SanJuan, E.: From term variants to research topics (2002) 0.00 
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    Date
    6. 1.1997 18:30:28
    Source
    Knowledge organization. 29(2002) nos.3/4, S.181-197
  12. Rosemblat, G.; Tse, T.; Gemoets, D.: Adapting a monolingual consumer health system for Spanish cross-language information retrieval (2004) 0.00 
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    Date
    6. 1.1997 18:30:28
    29. 8.2004 19:12:06
  13. Semantik, Lexikographie und Computeranwendungen : Workshop ... (Bonn) : 1995.01.27-28 (1996) 0.00 
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    Date
    14. 4.2007 10:04:22
  14. Kuhlen, R.: Morphologische Relationen durch Reduktionsalgorithmen (1974) 0.00 
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    Date
    29. 1.2011 14:56:29
  15. Barthel, J.; Ciesielski, R.: Regeln zu ChatGPT an Unis oft unklar : KI in der Bildung (2023) 0.00 
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  16. Jones, I.; Cunliffe, D.; Tudhope, D.: Natural language processing and knowledge organization systems as an aid to retrieval (2004) 0.00 
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  17. Rapp, R.: Text-Detektor : Fehlertolerantes Retrieval ganz einfach (1997) 0.00 
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  18. Wettler, M.; Rapp, R.; Ferber, R.: Freie Assoziationen und Kontiguitäten von Wörtern in Texten (1993) 0.00 
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  19. Warner, A.J.: Natural language processing (1987) 0.00 
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  20. Caseiro, D.: Automatic language identification bibliography : Last Update: 20 September 1999 (1999) 0.00 
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