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Semantic Classifier Approach to Document Classification

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Artificial Intelligence and Soft Computing (ICAISC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12415))

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Abstract

We propose a new document classification method, bridging discrepancies (so-called semantic gap) between the training set and the application sets of textual data. We demonstrate its superiority over classical text classification approaches, including traditional classifier ensembles. The method consists of combining a document categorization technique with a single classifier or a classifier ensemble.

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Notes

  1. 1.

    https://www.nlm.nih.gov/mesh/.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, ul. Jana Kazimierza 5, Warszawa, Poland

    Piotr Borkowski, Krzysztof Ciesielski & Mieczysław A. Kłopotek

Authors
  1. Piotr Borkowski
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  2. Krzysztof Ciesielski
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  3. Mieczysław A. Kłopotek
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Corresponding author

Correspondence to Piotr Borkowski .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

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

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Borkowski, P., Ciesielski, K., Kłopotek, M.A. (2020). Semantic Classifier Approach to Document Classification. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2020. Lecture Notes in Computer Science(), vol 12415. Springer, Cham. https://doi.org/10.1007/978-3-030-61401-0_61

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  • DOI: https://doi.org/10.1007/978-3-030-61401-0_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61400-3

  • Online ISBN: 978-3-030-61401-0

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