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Extraction and Interpretation of Textual Data from Czech Insolvency Proceedings

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10246))

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Abstract

Recently, the Czech Insolvency Register covers about 200000 insolvency proceedings. In order to better assess the real impact of indebtedness across the Czech society, the data about creditors or reasons for debt might be of great value. Unfortunately, the vast majority of such information is contained only in scanned document copies attached to the insolvency proceedings. Therefore, this study aims at finding efficient pre-processing, clustering and classification techniques capable of extracting the wanted information from these cca 1200000 pdf-files.

The first author was partially supported by the Czech Science Foundation under Grant No. 15-04960S. The second author was partially supported by the Charles University, project GA UK No. 120616.

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    http://www.abbyy.com/finereader/.

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Author information

Authors and Affiliations

  1. Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic

    Iveta Mrázová & Peter Zvirinský

Authors
  1. Iveta Mrázová
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  2. Peter Zvirinský
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Corresponding author

Correspondence to Iveta Mrázová .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Mrázová, I., Zvirinský, P. (2017). Extraction and Interpretation of Textual Data from Czech Insolvency Proceedings. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10246. Springer, Cham. https://doi.org/10.1007/978-3-319-59060-8_12

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  • DOI: https://doi.org/10.1007/978-3-319-59060-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59059-2

  • Online ISBN: 978-3-319-59060-8

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