Search (26 results, page 1 of 2)

  • × language_ss:"d"
  • × theme_ss:"Computerlinguistik"
  • × year_i:[2010 TO 2020}
  1. 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
    Type
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  2. Lezius, W.: Morphy - Morphologie und Tagging für das Deutsche (2013) 0.01
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    Date
    22. 3.2015 9:30:24
  3. Biselli, A.: Unter Generalverdacht durch Algorithmen (2014) 0.00
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  4. Karlova-Bourbonus, N.: Automatic detection of contradictions in texts (2018) 0.00
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    Abstract
    Natural language contradictions are of complex nature. As will be shown in Chapter 5, the realization of contradictions is not limited to the examples such as Socrates is a man and Socrates is not a man (under the condition that Socrates refers to the same object in the real world), which is discussed by Aristotle (Section 3.1.1). Empirical evidence (see Chapter 5 for more details) shows that only a few contradictions occurring in the real life are of that explicit (prototypical) kind. Rather, con-tradictions make use of a variety of natural language devices such as, e.g., paraphrasing, synonyms and antonyms, passive and active voice, diversity of negation expression, and figurative linguistic means such as idioms, irony, and metaphors. Additionally, the most so-phisticated kind of contradictions, the so-called implicit contradictions, can be found only when applying world knowledge and after conducting a sequence of logical operations such as e.g. in: (1.1) The first prize was given to the experienced grandmaster L. Stein who, in total, col-lected ten points (7 wins and 3 draws). Those familiar with the chess rules know that a chess player gets one point for winning and zero points for losing the game. In case of a draw, each player gets a half point. Built on this idea and by conducting some simple mathematical operations, we can infer that in the case of 7 wins and 3 draws (the second part of the sentence), a player can only collect 8.5 points and not 10 points. Hence, we observe that there is a contradiction between the first and the second parts of the sentence.
    Implicit contradictions will only partially be the subject of the present study, aiming primarily at identifying the realization mechanism and cues (Chapter 5) as well as finding the parts of contradictions by applying the state of the art algorithms for natural language processing without conducting deep meaning processing. Further in focus are the explicit and implicit contradictions that can be detected by means of explicit linguistic, structural, lexical cues, and by conducting some additional processing operations (e.g., counting the sum in order to detect contradictions arising from numerical divergencies). One should note that an additional complexity in finding contradictions can arise in case parts of the contradictions occur on different levels of realization. Thus, a contradiction can be observed on the word- and phrase-level, such as in a married bachelor (for variations of contradictions on lexical level, see Ganeev 2004), on the sentence level - between parts of a sentence or between two or more sentences, or on the text level - between the portions of a text or between the whole texts such as a contradiction between the Bible and the Quran, for example. Only contradictions arising at the level of single sentences occurring in one or more texts, as well as parts of a sentence, will be considered for the purpose of this study. Though the focus of interest will be on single sentences, it will make use of text particularities such as coreference resolution without establishing the referents in the real world. Finally, another aspect to be considered is that parts of the contradictions are not neces-sarily to appear at the same time. They can be separated by many years and centuries with or without time expression making their recognition by human and detection by machine challenging. According to Aristotle's ontological version of the LNC (Section 3.1.1), how-ever, the same time reference is required in order for two statements to be judged as a contradiction. Taking this into account, we set the borders for the study by limiting the ana-lyzed textual data thematically (only nine world events) and temporally (three days after the reported event had happened) (Section 5.1). No sophisticated time processing will thus be conducted.
  5. Altmann, E.G.; Cristadoro, G.; Esposti, M.D.: On the origin of long-range correlations in texts (2012) 0.00
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    Abstract
    The complexity of human interactions with social and natural phenomena is mirrored in the way we describe our experiences through natural language. In order to retain and convey such a high dimensional information, the statistical properties of our linguistic output has to be highly correlated in time. An example are the robust observations, still largely not understood, of correlations on arbitrary long scales in literary texts. In this paper we explain how long-range correlations flow from highly structured linguistic levels down to the building blocks of a text (words, letters, etc..). By combining calculations and data analysis we show that correlations take form of a bursty sequence of events once we approach the semantically relevant topics of the text. The mechanisms we identify are fairly general and can be equally applied to other hierarchical settings.
    Type
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  6. Engerer, V.: Indexierungstheorie für Linguisten : zu einigen natürlichsprachlichen Zügen in künstlichen Indexsprachen (2014) 0.00
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  7. Voss, O.: Übersetzer überflüssig? : Sprachsoftware DeepL und Acrolinx (2019) 0.00
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  8. Hahn, U.: Methodische Grundlagen der Informationslinguistik (2013) 0.00
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  9. Engerer, V.: Informationswissenschaft und Linguistik. : kurze Geschichte eines fruchtbaren interdisziplinäaren Verhäaltnisses in drei Akten (2012) 0.00
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  10. Wolfangel, E.: Ich verstehe (2017) 0.00
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  11. Holland, M.: Erstes wissenschaftliches Buch eines Algorithmus' veröffentlicht (2019) 0.00
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    Abstract
    Der Wissenschaftsverlag Springer Nature hat nach eigenen Angaben das erste Buch veröffentlicht, das von einem Algorithmus verfasst wurde. Bei Springer Nature ist das nach Angaben des Wissenschaftsverlags erste maschinengenerierte Buch erschienen: "Lithium-Ion Batteries - A Machine-Generated Summary of Current Research" biete einen Überblick über die neuesten Forschungspublikationen über Lithium-Ionen-Batterien, erklärte die Goethe-Universität Frankfurt am Main. Dort wurde im Bereich Angewandte Computerlinguistik unter der Leitung von Christian Chiarcos jenes Verfahren entwickelt, das Textinhalte automatisch analysiert und relevante Publikationen auswählen kann. Es heißt "Beta Writer" und steht als Autor über dem Buch.
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  12. Heid, U.: Computerlinguistik zwischen Informationswissenschaft und multilingualer Kommunikation (2010) 0.00
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  13. Becks, D.; Schulz, J.M.: Domänenübergreifende Phrasenextraktion mithilfe einer lexikonunabhängigen Analysekomponente (2010) 0.00
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  14. Ludwig, B.; Reischer, J.: Informationslinguistik in Regensburg (2012) 0.00
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  15. Baierer, K.; Zumstein, P.: Verbesserung der OCR in digitalen Sammlungen von Bibliotheken (2016) 0.00
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  16. Franke-Maier, M.: Computerlinguistik und Bibliotheken : Editorial (2016) 0.00
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    Editor
    Ledl, A.
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  17. Strube, M.: Kreativ durch Analogien (2011) 0.00
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  18. Rötzer, F.: Kann KI mit KI generierte Texte erkennen? (2019) 0.00
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  19. Budin, G.: Zum Entwicklungsstand der Terminologiewissenschaft (2019) 0.00
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  20. Sünkler, S.; Kerkmann, F.; Schultheiß, S.: Ok Google . the end of search as we know it : sprachgesteuerte Websuche im Test (2018) 0.00
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