Search (16 results, page 1 of 1)

  • × theme_ss:"Computerlinguistik"
  • × year_i:[2010 TO 2020}
  1. Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012) 0.05 
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    Date
    10. 1.2013 19:22:47
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    x
  2. Wong, W.; Liu, W.; Bennamoun, M.: Ontology learning from text : a look back and into the future (2010) 0.03 
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    Content
    Pre-publication version für: ACM Computing Surveys, Vol. X, No. X, Article X, Publication date: X 2011.
  3. Schmolz, H.: Anaphora resolution and text retrieval : a lnguistic analysis of hypertexts (2015) 0.02 
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  4. Schmolz, H.: Anaphora resolution and text retrieval : a lnguistic analysis of hypertexts (2013) 0.02 
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  5. Scherer Auberson, K.: Counteracting concept drift in natural language classifiers : proposal for an automated method (2018) 0.01 
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  6. Lu, K.; Cai, X.; Ajiferuke, I.; Wolfram, D.: Vocabulary size and its effect on topic representation (2017) 0.01 
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  7. Lezius, W.: Morphy - Morphologie und Tagging für das Deutsche (2013) 0.01 
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    Date
    22. 3.2015 9:30:24
  8. Renker, L.: Exploration von Textkorpora : Topic Models als Grundlage der Interaktion (2015) 0.01 
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  9. Bredack, J.: Automatische Extraktion fachterminologischer Mehrwortbegriffe : ein Verfahrensvergleich (2016) 0.01 
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  10. Reyes Ayala, B.; Knudson, R.; Chen, J.; Cao, G.; Wang, X.: Metadata records machine translation combining multi-engine outputs with limited parallel data (2018) 0.01 
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  11. Lawrie, D.; Mayfield, J.; McNamee, P.; Oard, P.W.: Cross-language person-entity linking from 20 languages (2015) 0.01 
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    Abstract
    The goal of entity linking is to associate references to an entity that is found in unstructured natural language content to an authoritative inventory of known entities. This article describes the construction of 6 test collections for cross-language person-entity linking that together span 22 languages. Fully automated components were used together with 2 crowdsourced validation stages to affordably generate ground-truth annotations with an accuracy comparable to that of a completely manual process. The resulting test collections each contain between 642 (Arabic) and 2,361 (Romanian) person references in non-English texts for which the correct resolution in English Wikipedia is known, plus a similar number of references for which no correct resolution into English Wikipedia is believed to exist. Fully automated cross-language person-name linking experiments with 20 non-English languages yielded a resolution accuracy of between 0.84 (Serbian) and 0.98 (Romanian), which compares favorably with previously reported cross-language entity linking results for Spanish.
  12. Nagy T., I.: Detecting multiword expressions and named entities in natural language texts (2014) 0.01 
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  13. Fóris, A.: Network theory and terminology (2013) 0.01 
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    Date
    2. 9.2014 21:22:48
  14. Karlova-Bourbonus, N.: Automatic detection of contradictions in texts (2018) 0.01 
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  15. 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
  16. Deventer, J.P. van; Kruger, C.J.; Johnson, R.D.: Delineating knowledge management through lexical analysis : a retrospective (2015) 0.01 
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    Date
    20. 1.2015 18:30:22

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