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  • × theme_ss:"Computerlinguistik"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.08 
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    Abstract
    Document representations for text classification are typically based on the classical Bag-Of-Words paradigm. This approach comes with deficiencies that motivate the integration of features on a higher semantic level than single words. In this paper we propose an enhancement of the classical document representation through concepts extracted from background knowledge. Boosting is used for actual classification. Experimental evaluations on two well known text corpora support our approach through consistent improvement of the results.
    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
    Type
    a
  2. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.07 
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    Abstract
    This research revisits the classic Turing test and compares recent large language models such as ChatGPT for their abilities to reproduce human-level comprehension and compelling text generation. Two task challenges- summary and question answering- prompt ChatGPT to produce original content (98-99%) from a single text entry and sequential questions initially posed by Turing in 1950. We score the original and generated content against the OpenAI GPT-2 Output Detector from 2019, and establish multiple cases where the generated content proves original and undetectable (98%). The question of a machine fooling a human judge recedes in this work relative to the question of "how would one prove it?" The original contribution of the work presents a metric and simple grammatical set for understanding the writing mechanics of chatbots in evaluating their readability and statistical clarity, engagement, delivery, overall quality, and plagiarism risks. While Turing's original prose scores at least 14% below the machine-generated output, whether an algorithm displays hints of Turing's true initial thoughts (the "Lovelace 2.0" test) remains unanswerable.
    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
    Type
    a
  3. Lezius, W.; Rapp, R.; Wettler, M.: ¬A morphology-system and part-of-speech tagger for German (1996) 0.05 
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    Date
    22. 3.2015 9:37:18
    Type
    a
  4. Kay, M.: ¬The proper place of men and machines in language translation (1997) 0.04 
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    Abstract
    Machine translation stands no chance of filling actual needs for translation because, although there has been progress in relevant areas of computer science, advance in linguistics have not touched the core problems. Cooperative man-machine systems need to be developed, Proposes a translator's amanuensis, incorporating into a word processor some simple facilities peculiar to translation. Gradual enhancements of such a system could lead to the original goal of machine translation
    Content
    Reprint of a Xerox PARC Working Paper which appeared in 1980
    Date
    31. 7.1996 9:22:19
    Footnote
    Contribution to a special issue devoted to the theme of new tools for human translators
    Type
    a
  5. Melby, A.: Some notes on 'The proper place of men and machines in language translation' (1997) 0.04 
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    Abstract
    Responds to Kay, M.: The proper place of men and machines in language translation. Examines the appropriateness of machine translation (MT) under the following special circumstances: controlled domain-specific text and high-quality output; controlled domain-specific text and indicative output; dynamic general text and indicative output and dynamic general text and high-quality output. MT is appropriate in the 1st 3 cases but the 4th case requires human translation. Examines how MT research could be more useful for aiding human translation
    Date
    31. 7.1996 9:22:19
    Footnote
    Contribution to a special issue devoted to the theme of new tools for human translators
    Type
    a
  6. Warner, A.J.: Natural language processing (1987) 0.04 
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    Source
    Annual review of information science and technology. 22(1987), S.79-108
    Type
    a
  7. Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991) 0.03 
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    Date
    8.10.2000 11:52:22
    Source
    Library science with a slant to documentation. 28(1991) no.4, S.125-130
    Type
    a
  8. McMahon, J.G.; Smith, F.J.: Improved statistical language model performance with automatic generated word hierarchies (1996) 0.03 
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    Source
    Computational linguistics. 22(1996) no.2, S.217-248
    Type
    a
  9. Somers, H.: Example-based machine translation : Review article (1999) 0.03 
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    Date
    31. 7.1996 9:22:19
    Type
    a
  10. New tools for human translators (1997) 0.03 
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    Abstract
    A special issue devoted to the theme of new tools for human tranlators
    Date
    31. 7.1996 9:22:19
  11. Baayen, R.H.; Lieber, H.: Word frequency distributions and lexical semantics (1997) 0.03 
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    Date
    28. 2.1999 10:48:22
    Type
    a
  12. ¬Der Student aus dem Computer (2023) 0.03 
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  13. Computational linguistics for the new millennium : divergence or synergy? Proceedings of the International Symposium held at the Ruprecht-Karls Universität Heidelberg, 21-22 July 2000. Festschrift in honour of Peter Hellwig on the occasion of his 60th birthday (2002) 0.03 
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    Abstract
    The two seemingly conflicting tendencies, synergy and divergence, are both fundamental to the advancement of any science. Their interplay defines the demarcation line between application-oriented and theoretical research. The papers in this festschrift in honour of Peter Hellwig are geared to answer questions that arise from this insight: where does the discipline of Computational Linguistics currently stand, what has been achieved so far and what should be done next. Given the complexity of such questions, no simple answers can be expected. However, each of the practitioners and researchers are contributing from their very own perspective a piece of insight into the overall picture of today's and tomorrow's computational linguistics.
    Content
    Contents: Manfred Klenner / Henriette Visser: Introduction - Khurshid Ahmad: Writing Linguistics: When I use a word it means what I choose it to mean - Jürgen Handke: 2000 and Beyond: The Potential of New Technologies in Linguistics - Jurij Apresjan / Igor Boguslavsky / Leonid Iomdin / Leonid Tsinman: Lexical Functions in NU: Possible Uses - Hubert Lehmann: Practical Machine Translation and Linguistic Theory - Karin Haenelt: A Contextbased Approach towards Content Processing of Electronic Documents - Petr Sgall / Eva Hajicová: Are Linguistic Frameworks Comparable? - Wolfgang Menzel: Theory and Applications in Computational Linguistics - Is there Common Ground? - Robert Porzel / Michael Strube: Towards Context-adaptive Natural Language Processing Systems - Nicoletta Calzolari: Language Resources in a Multilingual Setting: The European Perspective - Piek Vossen: Computational Linguistics for Theory and Practice.
    Editor
    Klenner, M. u. H. Visser
    Type
    m
  14. Sienel, J.; Weiss, M.; Laube, M.: Sprachtechnologien für die Informationsgesellschaft des 21. Jahrhunderts (2000) 0.03 
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    26.12.2000 13:22:17
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  15. 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) 0.03 
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  16. Boleda, G.; Evert, S.: Multiword expressions : a pain in the neck of lexical semantics (2009) 0.03 
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  17. Monnerjahn, P.: Vorsprung ohne Technik : Übersetzen: Computer und Qualität (2000) 0.03 
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  18. Pinker, S.: Wörter und Regeln : Die Natur der Sprache (2000) 0.03 
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    Date
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    Footnote
    Rez. in: Franfurter Rundschau Nr.43 vom 20.2.2001, S.23 (A. Barthelmy)
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  19. Way, E.C.: Knowledge representation and metaphor (oder: meaning) (1994) 0.02 
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    Bereits 1991 bei Kluwer publiziert // Rez. in: Knowledge organization 22(1995) no.1, S.48-49 (O. Sechser)
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  20. Ruge, G.: Sprache und Computer : Wortbedeutung und Termassoziation. Methoden zur automatischen semantischen Klassifikation (1995) 0.02 
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    Rez. in: Knowledge organization 22(1995) no.3/4, S.182-184 (M.T. Rolland)
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