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Ontology-Based Conceptualisation of Text Mining Practice Areas for Education

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Computational Collective Intelligence (ICCCI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11684))

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Abstract

Text mining is highly multi-disciplinary field including various techniques of text analysis. These techniques are used for uncovering hidden information and knowledge in semi-structured and non-structured texts. Text mining concepts are spread among different, but related practice areas. It is often difficult to receive fast insight into this amount of concepts for a non-professional, e.g. for a student. The paper presents the OWL ontology-based prototype which should ease education and learning of facts which are used in the text mining domain. It is mainly aimed to the university students studying text mining at the introductory level. It can also be used as a formal vocabulary of text mining concepts for understanding of methods, techniques, concepts and relations between them by machines.

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Acknowledgements

The support of the Specific research project at FIM UHK is gratefully acknowledged. The author would like to thank Tomáš Nacházel for figures preparation and Luboš Mercl for administration.

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Authors and Affiliations

  1. Faculty of Informatics and Management, University of Hradec Králové, Rokitanského 62, 500 03, Hradec Králové, Czech Republic

    Martina Husáková

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  1. Martina Husáková
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Correspondence to Martina Husáková .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. University of Pau and Pays de l'Adour, Pau, France

    Richard Chbeir

  3. University of Pau and Pays de l'Adour, Pau, France

    Ernesto Exposito

  4. University of Pau and Pays de l'Adour, Pau, France

    Philippe Aniorté

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Husáková, M. (2019). Ontology-Based Conceptualisation of Text Mining Practice Areas for Education. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11684. Springer, Cham. https://doi.org/10.1007/978-3-030-28374-2_46

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  • DOI: https://doi.org/10.1007/978-3-030-28374-2_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-28373-5

  • Online ISBN: 978-3-030-28374-2

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