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Term Extraction from German Computer Science Textbooks

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Data Mining and Big Data (DMBD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9714))

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Abstract

It is widely accepted that it is important to use a proper Computer Science terminology to communicate with other computer scientists. To learn Computer Science concepts students also need to speak about topics in school meaningfully. This article reports a method to identify German Computer Science terms for teaching from a set of German textbooks and web pages. It identifies future work to create a suitable German Computer Science Education terminology.

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References

  1. Diethelm, I., Goschler, J.: Questions on spoken language and terminology for teaching computer science. In: ITiCSE 2015, Vilnius (2015)

    Google Scholar 

  2. Heyer, G., Quasthoff, U., Wittig, T.: Text Mining: Wissensrohstoff Text: Konzepte, Algorithmen, Ergebnisse. W3L GmbH, Herdecke (2012). Second reprint edition

    Google Scholar 

  3. Holmboe, C.: Conceptualization and labelling as cognitive challenges for students of data modelling. Comput. Sci. Educ. 15(2), 143–161 (2005). http://dx.doi.org/10.1080/08993400500150796

    Article  Google Scholar 

  4. Kim, S.N., Cavedon, L.: Classify domain-specific terms using a dictionary. In: Proceedings of the ALTA (2011)

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  5. Weiss, S.M., Indurkhya, N., Zhang, T.: Fundamentals of Predictive Text Mining, 1st edn, pp. 13–39. Springer, London (2010)

    MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computing Science, Carl von Ossietzky University of Oldenburg, Ammerländer Heerstr. 114-118, 26129, Oldenburg, Germany

    Kevin Möhlmann & Jörn Syrbe

Authors
  1. Kevin Möhlmann
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  2. Jörn Syrbe
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Corresponding author

Correspondence to Jörn Syrbe .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

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© 2016 Springer International Publishing Switzerland

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Cite this paper

Möhlmann, K., Syrbe, J. (2016). Term Extraction from German Computer Science Textbooks. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_21

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  • DOI: https://doi.org/10.1007/978-3-319-40973-3_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40972-6

  • Online ISBN: 978-3-319-40973-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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