Search (121 results, page 1 of 7)

  • × theme_ss:"Computerlinguistik"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.15
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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. Winograd, T.: Understanding natural language (1972) 0.03
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  3. Meng, K.; Ba, Z.; Ma, Y.; Li, G.: ¬A network coupling approach to detecting hierarchical linkages between science and technology (2024) 0.03
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    Abstract
    Detecting science-technology hierarchical linkages is beneficial for understanding deep interactions between science and technology (S&T). Previous studies have mainly focused on linear linkages between S&T but ignored their structural linkages. In this paper, we propose a network coupling approach to inspect hierarchical interactions of S&T by integrating their knowledge linkages and structural linkages. S&T knowledge networks are first enhanced with bidirectional encoder representation from transformers (BERT) knowledge alignment, and then their hierarchical structures are identified based on K-core decomposition. Hierarchical coupling preferences and strengths of the S&T networks over time are further calculated based on similarities of coupling nodes' degree distribution and similarities of coupling edges' weight distribution. Extensive experimental results indicate that our approach is feasible and robust in identifying the coupling hierarchy with superior performance compared to other isomorphism and dissimilarity algorithms. Our research extends the mindset of S&T linkage measurement by identifying patterns and paths of the interaction of S&T hierarchical knowledge.
  4. Ontologie und Axiomatik der Wissensbasis von LILOG (1992) 0.03
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    Editor
    Klose, G., E. Lang u. T. Pirlein
  5. Winograd, T.: ¬Ein prozedurales Modell des Sprachverstehens (1977) 0.03
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  6. Strzalkowski, T.: Reversible grammar in natural langugae processing (19??) 0.03
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  7. Perez-Carballo, J.; Strzalkowski, T.: Natural language information retrieval : progress report (2000) 0.03
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  8. Pirkola, A.; Hedlund, T.; Keskustalo, H.; Järvelin, K.: Dictionary-based cross-language information retrieval : problems, methods, and research findings (2001) 0.03
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  9. Nakagawa, H.; Mori, T.: Automatic term recognition based an statistics of compound nouns and their components (2003) 0.03
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  10. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.03
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  11. Warner, A.J.: Natural language processing (1987) 0.03
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    Source
    Annual review of information science and technology. 22(1987), S.79-108
  12. Graham, T.: ¬The free language approach to online catalogues : the user (1985) 0.03
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  13. Samad, T.: ¬A natural language interface for computer aided design (19??) 0.03
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  14. Koppel, M.; Akiva, N.; Dagan, I.: Feature instability as a criterion for selecting potential style markers (2006) 0.03
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    Abstract
    We introduce a new measure on linguistic features, called stability, which captures the extent to which a language element such as a word or a syntactic construct is replaceable by semantically equivalent elements. This measure may be perceived as quantifying the degree of available "synonymy" for a language item. We show that frequent, but unstable, features are especially useful as discriminators of an author's writing style.
  15. McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996) 0.02
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    Source
    Computational linguistics. 22(1996) no.2, S.217-248
  16. Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991) 0.02
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    Date
    8.10.2000 11:52:22
  17. Somers, H.: Example-based machine translation : Review article (1999) 0.02
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    Date
    31. 7.1996 9:22:19
  18. New tools for human translators (1997) 0.02
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    Date
    31. 7.1996 9:22:19
  19. Baayen, R.H.; Lieber, H.: Word frequency distributions and lexical semantics (1997) 0.02
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    Date
    28. 2.1999 10:48:22
  20. ¬Der Student aus dem Computer (2023) 0.02
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    Date
    27. 1.2023 16:22:55

Languages

  • e 83
  • d 36
  • m 1
  • More… Less…

Types

  • a 94
  • el 15
  • m 14
  • s 9
  • x 3
  • d 2
  • p 2
  • More… Less…

Classifications