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Enhancing Concept Extraction from Polish Texts with Rule Management

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Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery (BDAS 2015, BDAS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 613))

Abstract

This paper presents a system for extraction of concepts from unstructured Polish texts. Here concepts are understood as n-grams, whose words satisfy specific grammatical constraints. Detection and transformation of concepts to their normalized form are performed with rules defined in a language, which combines elements of colored and fuzzy Petri nets. We apply a user friendly method for specification of samples of transformation patterns that are further compiled to rules. To improve accuracy and performance, we recently introduced rule management mechanisms, which are based on two relations between rules: partial refinement and covering. The implemented methods include filtering with metarules and removal of redundant rules (i.e. these covered by other rules). We report results of experiments, which aimed at extracting specific concepts (actions) using a ruleset refactored with the developed rule management techniques.

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Authors and Affiliations

  1. AGH University of Science and Technology, Mickiewicza Av. 30, 30-059, Kraków, Poland

    Piotr Szwed

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  1. Piotr Szwed
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Correspondence to Piotr Szwed .

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Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Dariusz Mrozek

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Paweł Kasprowski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Daniel Kostrzewa

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Szwed, P. (2016). Enhancing Concept Extraction from Polish Texts with Rule Management. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery. BDAS BDAS 2015 2016. Communications in Computer and Information Science, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-34099-9_27

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  • DOI: https://doi.org/10.1007/978-3-319-34099-9_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-34098-2

  • Online ISBN: 978-3-319-34099-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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