Search (123 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) 0.05 
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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. Cruys, T. van de; Moirón, B.V.: Semantics-based multiword expression extraction (2007) 0.04 
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    Date
    29. 4.2016 12:14:04
    Source
    Proceedings of the Workshop on A Broader Perspective on Multiword Expressions, Prag 2007
    Year
    2007
  3. Frederichs, A.: Natürlichsprachige Abfrage und 3-D-Visualisierung von Wissenszusammenhängen (2007) 0.03 
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    Date
    25.10.2007 9:51:29
    Source
    Wa(h)re Information: 29. Österreichischer Bibliothekartag Bregenz, 19.-23.9.2006. Hrsg.: Harald Weigel
    Year
    2007
  4. Geißler, S.: Maschinelles Lernen und NLP : Reif für die industrielle Anwendung! (2019) 0.02 
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    Content
    Vgl.: https://doi.org/10.1515/iwp-2019-2007.
    Date
    2. 9.2019 19:29:24
  5. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.02 
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  6. Schneider, R.: Question answering : das Retrieval der Zukunft? (2007) 0.02 
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    Source
    Zeitschrift für Bibliothekswesen und Bibliographie. 54(2007) H.1, S.3-11
    Year
    2007
  7. Melby, A.: Some notes on 'The proper place of men and machines in language translation' (1997) 0.02 
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    Date
    31. 7.1996 9:22:19
    Source
    Machine translation. 12(1997) nos.1/2, S.29-34
  8. Melucci, M.; Orio, N.: Design, implementation, and evaluation of a methodology for automatic stemmer generation (2007) 0.02 
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    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.5, S.673-686
    Year
    2007
  9. Doszkocs, T.E.; Zamora, A.: Dictionary services and spelling aids for Web searching (2004) 0.01 
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    Date
    14. 8.2004 17:22:56
    Source
    Online. 28(2004) no.3, S.22-29
  10. Warner, J.: Linguistics and information theory : analytic advantages (2007) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.2, S.275-285
    Year
    2007
  11. Argamon, S.; Whitelaw, C.; Chase, P.; Hota, S.R.; Garg, N.; Levitan, S.: Stylistic text classification using functional lexical features (2007) 0.01 
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    Journal of the American Society for Information Science and Technology. 58(2007) no.6, S.802-822
    Year
    2007
  12. Santana Suárez, O.; Carreras Riudavets, F.J.; Hernández Figueroa, Z.; González Cabrera, A.C.: Integration of an XML electronic dictionary with linguistic tools for natural language processing (2007) 0.01 
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    Source
    Information processing and management. 43(2007) no.4, S.946-957
    Year
    2007
  13. Niemi, T.; Jämsen, J.: ¬A query language for discovering semantic associations, part II : sample queries and query evaluation (2007) 0.01 
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    Abstract
    In our query language introduced in Part I (Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1559-1568) the user can formulate queries to find out (possibly complex) semantic relationships among entities. In this article we demonstrate the usage of our query language and discuss the new applications that it supports. We categorize several query types and give sample queries. The query types are categorized based on whether the entities specified in a query are known or unknown to the user in advance, and whether text information in documents is utilized. Natural language is used to represent the results of queries in order to facilitate correct interpretation by the user. We discuss briefly the issues related to the prototype implementation of the query language and show that an independent operation like Rho (Sheth et al., 2005; Anyanwu & Sheth, 2002, 2003), which presupposes entities of interest to be known in advance, is exceedingly inefficient in emulating the behavior of our query language. The discussion also covers potential problems, and challenges for future work.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1686-1700
    Year
    2007
  14. Niemi, T.; Jämsen , J.: ¬A query language for discovering semantic associations, part I : approach and formal definition of query primitives (2007) 0.01 
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    Content
    Part II: Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1686-1700.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1559-1568
    Year
    2007
  15. Kuhlen, R.: Morphologische Relationen durch Reduktionsalgorithmen (1974) 0.01 
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    Date
    29. 1.2011 14:56:29
  16. Warner, J.: Analogies between linguistics and information theory (2007) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.3, S.309-321
    Year
    2007
  17. Wang, F.L.; Yang, C.C.: Mining Web data for Chinese segmentation (2007) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.12, S.1820-1837
    Year
    2007
  18. Peng, F.; Huang, X.: Machine learning for Asian language text classification (2007) 0.01 
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