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Big Data in Contemporary Linguistic Research. In Search of Optimum Methods for Language Chronologization

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Book cover Intelligent Information and Database Systems (ACIIDS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9621))

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Abstract

The paper will concern the theoretical and practical problems of analysing the mass of linguistic data which has arisen in conjunction with the development of many fields of life. Moreover, the universe of texts is growing every day – both forwards and backwards. Forwards because every new article, book, blog, e-mail or text message expands the set of existing texts; and backwards because the same set is also expanded whenever a scan is made of another historical text. Our knowledge about past times is growing by leaps and bounds. We are therefore particularly interested in the analysis of historical texts that can be carried out in the second decade of the 21st century.

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Authors and Affiliations

  1. Institute of Linguistics, Adam Mickiewicz University, Poznań, Poland

    Piotr Wierzchoń

Authors
  1. Piotr Wierzchoń
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Correspondence to Piotr Wierzchoń .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

  3. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

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Wierzchoń, P. (2016). Big Data in Contemporary Linguistic Research. In Search of Optimum Methods for Language Chronologization. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_14

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  • DOI: https://doi.org/10.1007/978-3-662-49381-6_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49380-9

  • Online ISBN: 978-3-662-49381-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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