Search (55 results, page 1 of 3)

  • × theme_ss:"Computerlinguistik"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.31
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    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  2. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.20
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  3. Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012) 0.16
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    Content
    A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.
    Date
    10. 1.2013 19:22:47
  4. Pinker, S.: Wörter und Regeln : Die Natur der Sprache (2000) 0.04
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    Abstract
    Wie lernen Kinder sprechen? Welche Hinweise geben gerade ihre Fehler beim Spracherwerb auf den Ablauf des Lernprozesses - getreu dem Motto: "Kinder sagen die töllsten Sachen«? Und wie helfen beziehungsweise warum scheitern bislang Computer bei der Simulation neuronaler Netzwerke, die am komplizierten Gewebe der menschlichen Sprache mitwirken? In seinem neuen Buch Wörter und Regeln hat der bekannte US-amerikanische Kognitionswissenschaftler Steven Pinker (Der Sprachinstinkt) wieder einmal eine ebenso informative wie kurzweifige Erkundungstour ins Reich der Sprache unternommen. Was die Sache besonders spannend und lesenswert macht: Souverän beleuchtet der Professor am Massachusetts Institute of Technology sowohl natur- als auch geisteswissenschaftliche Aspekte. So vermittelt er einerseits linguistische Grundlagen in den Fußspuren Ferdinand de Saussures, etwa die einer generativen Grammatik, liefert einen Exkurs durch die Sprachgeschichte und widmet ein eigenes Kapitel den Schrecken der deutschen Sprache". Andererseits lässt er aber auch die neuesten bildgebenden Verfahren nicht außen vor, die zeigen, was im Gehirn bei der Sprachverarbeitung abläuft. Pinkers Theorie, die sich in diesem Puzzle verschiedenster Aspekte wiederfindet: Sprache besteht im Kein aus zwei Bestandteilen - einem mentalen Lexikon aus erinnerten Wörtern und einer mentalen Grammatik aus verschiedenen kombinatorischen Regeln. Konkret heißt das: Wir prägen uns bekannte Größen und ihre abgestuften, sich kreuzenden Merkmale ein, aber wir erzeugen auch neue geistige Produkte, in dem wir Regeln anwenden. Gerade daraus, so schließt Pinker, erschließt sich der Reichtum und die ungeheure Ausdruckskraft unserer Sprache
    Date
    19. 7.2002 14:22:31
  5. Wilhelm, K.: ¬Die Macht der Grammatik (2000) 0.03
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    Abstract
    Mit neuen bildgebenden Verfahren können Forscher dem Gehirn zusehen, wie es Sprache verarbeitet. Dabei zeigt sich: Nicht eine möglichst große Vielfalt von Wörtern, sondern erst deren sinnvolle Verknüpfung zu Sätzen, Syntax, bildet den Kern der menschlichen Sprache
  6. Schulz, A.: Motivierte Maschinen : Sprachcomputer (2002) 0.03
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    Source
    Gehirn und Geist: Das Magazin für Hirnforschung und Psychologie. 2002, H.3, S.54-56
  7. Warner, A.J.: Natural language processing (1987) 0.02
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    Source
    Annual review of information science and technology. 22(1987), S.79-108
  8. McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996) 0.01
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    Source
    Computational linguistics. 22(1996) no.2, S.217-248
  9. Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991) 0.01
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    Date
    8.10.2000 11:52:22
  10. Somers, H.: Example-based machine translation : Review article (1999) 0.01
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    Date
    31. 7.1996 9:22:19
  11. New tools for human translators (1997) 0.01
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    Date
    31. 7.1996 9:22:19
  12. Baayen, R.H.; Lieber, H.: Word frequency distributions and lexical semantics (1997) 0.01
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    Date
    28. 2.1999 10:48:22
  13. ¬Der Student aus dem Computer (2023) 0.01
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    Date
    27. 1.2023 16:22:55
  14. 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) 0.01
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    Date
    15. 3.2000 10:22:37
  15. Boleda, G.; Evert, S.: Multiword expressions : a pain in the neck of lexical semantics (2009) 0.01
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    Date
    1. 3.2013 14:56:22
  16. Monnerjahn, P.: Vorsprung ohne Technik : Übersetzen: Computer und Qualität (2000) 0.01
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    Source
    c't. 2000, H.22, S.230-231
  17. Menge-Sonnentag, R.: Google veröffentlicht einen Parser für natürliche Sprache (2016) 0.01
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    Content
    "Syntaktische Beziehungen Der Parser teilt den Wörtern eine syntaktische Funktion zu und untersucht die syntaktischen Beziehungen zwischen den Einzelteilen. Den englischen Beispielsatz aus dem Blog-Beitrag "Alice saw Bob" analysiert er folgendermaßen: "Alice" und "Bob" sind Substantive, und "saw" ist ein Verb. Letzteres ist gleichzeitig die Wurzel (ROOT), von der die restlichen Beziehungen ausgehen. Alice ist das zugehörige Subjekt (nsubj) und Bob das Objekt (dobj). Längere Sätze werden leicht mehrdeutig. Beispielsweise ist im Satz "Alice sah Bob mit dem Fernglas" nicht erkennbar, wer von den beiden das Fernglas in der Hand hält. Rein syntaktisch ist auch der Satz "Peter schneidet das Brot mit Sonnenblumenkernen" mehrdeutig. Das menschliche Gehirn erkennt die richtige Bedeutung recht zuverlässig, aber für maschinelle Parser stellen sie eine Herausforderung dar.
  18. Hutchins, J.: From first conception to first demonstration : the nascent years of machine translation, 1947-1954. A chronology (1997) 0.01
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    Date
    31. 7.1996 9:22:19
  19. Kuhlmann, U.; Monnerjahn, P.: Sprache auf Knopfdruck : Sieben automatische Übersetzungsprogramme im Test (2000) 0.01
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    Source
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  20. Lezius, W.; Rapp, R.; Wettler, M.: ¬A morphology-system and part-of-speech tagger for German (1996) 0.01
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    Date
    22. 3.2015 9:37:18

Years

Languages

  • e 36
  • d 19

Types

  • a 43
  • el 6
  • m 5
  • s 3
  • p 2
  • x 2
  • d 1
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