Search (18 results, page 1 of 1)

  • × theme_ss:"Computerlinguistik"
  • × type_ss:"el"
  • × year_i:[2010 TO 2020}
  1. Snajder, J.: Distributional semantics of multi-word expressions (2013) 0.01 
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    Date
    29. 4.2016 12:04:50
    Language
    e
  2. Baierer, K.; Zumstein, P.: Verbesserung der OCR in digitalen Sammlungen von Bibliotheken (2016) 0.01 
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  3. Stoykova, V.; Petkova, E.: Automatic extraction of mathematical terms for precalculus (2012) 0.01 
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    Date
    29. 5.2012 10:17:08
    Language
    e
  4. Snajder, J.; Almic, P.: Modeling semantic compositionality of Croatian multiword expressions (2015) 0.00 
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    Date
    29. 4.2016 12:42:17
    Language
    e
  5. RWI/PH: Auf der Suche nach dem entscheidenden Wort : die Häufung bestimmter Wörter innerhalb eines Textes macht diese zu Schlüsselwörtern (2012) 0.00 
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    Content
    "Die Dresdner Wissenschaftler haben die semantischen Eigenschaften von Texten mathematisch untersucht, indem sie zehn verschiedene englische Texte in unterschiedlichen Formen kodierten. Dazu zählt unter anderem die englische Ausgabe von Leo Tolstois "Krieg und Frieden". Beispielsweise übersetzten die Forscher Buchstaben innerhalb eines Textes in eine Binär-Sequenz. Dazu ersetzten sie alle Vokale durch eine Eins und alle Konsonanten durch eine Null. Mit Hilfe weiterer mathematischer Funktionen beleuchteten die Wissenschaftler dabei verschiedene Ebenen des Textes, also sowohl einzelne Vokale, Buchstaben als auch ganze Wörter, die in verschiedenen Formen kodiert wurden. Innerhalb des ganzen Textes lassen sich so wiederkehrende Muster finden. Diesen Zusammenhang innerhalb des Textes bezeichnet man als Langzeitkorrelation. Diese gibt an, ob zwei Buchstaben an beliebig weit voneinander entfernten Textstellen miteinander in Verbindung stehen - beispielsweise gibt es wenn wir an einer Stelle einen Buchstaben "K" finden, eine messbare höhere Wahrscheinlichkeit den Buchstaben "K" einige Seiten später nochmal zu finden. "Es ist zu erwarten, dass wenn es in einem Buch an einer Stelle um Krieg geht, die Wahrscheinlichkeit hoch ist das Wort Krieg auch einige Seiten später zu finden. Überraschend ist es, dass wir die hohe Wahrscheinlichkeit auch auf der Buchstabenebene finden", so Altmann.
  6. Sprachtechnologie : ein Überblick (2012) 0.00 
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    Theme
    Grundlagen u. Einführungen: Allgemeine Literatur
  7. Lezius, W.: Morphy - Morphologie und Tagging für das Deutsche (2013) 0.00 
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    Date
    22. 3.2015 9:30:24
  8. Liu, P.J.; Saleh, M.; Pot, E.; Goodrich, B.; Sepassi, R.; Kaiser, L.; Shazeer, N.: Generating Wikipedia by summarizing long sequences (2018) 0.00 
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  9. Kiela, D.; Clark, S.: Detecting compositionality of multi-word expressions using nearest neighbours in vector space models (2013) 0.00 
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  10. Rötzer, F.: KI-Programm besser als Menschen im Verständnis natürlicher Sprache (2018) 0.00 
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    Date
    22. 1.2018 11:32:44
  11. Wong, W.; Liu, W.; Bennamoun, M.: Ontology learning from text : a look back and into the future (2010) 0.00 
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  12. Shen, M.; Liu, D.-R.; Huang, Y.-S.: Extracting semantic relations to enrich domain ontologies (2012) 0.00 
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  13. Spitkovsky, V.I.; Chang, A.X.: ¬A cross-lingual dictionary for english Wikipedia concepts (2012) 0.00 
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  14. Perovsek, M.; Kranjca, J.; Erjaveca, T.; Cestnika, B.; Lavraca, N.: TextFlows : a visual programming platform for text mining and natural language processing (2016) 0.00 
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  15. Zadeh, B.Q.; Handschuh, S.: ¬The ACL RD-TEC : a dataset for benchmarking terminology extraction and classification in computational linguistics (2014) 0.00 
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  16. Rajasurya, S.; Muralidharan, T.; Devi, S.; Swamynathan, S.: Semantic information retrieval using ontology in university domain (2012) 0.00 
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  17. Spitkovsky, V.; Norvig, P.: From words to concepts and back : dictionaries for linking text, entities and ideas (2012) 0.00 
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  18. Nagy T., I.: Detecting multiword expressions and named entities in natural language texts (2014) 0.00 
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  • e 13
  • d 5

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