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Asian Conference on Intelligent Information and Database Systems

ACIIDS 2016: Intelligent Information and Database Systems pp 54–64Cite as

An Ontology-Based Knowledge Representation of MCDA Methods

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9621))

Abstract

Multiple-criteria decision analysis methods are widely used as tools supporting a decision problem. The article presents the taxonomy of the methods, which takes into consideration the most essential characteristics. This taxonomy, in the conceptualization process, was written by means of description logic and then it was implemented in the OWL language in the form of ontology representing field knowledge in the scope of MCDA methods. The research also considers the ontology verification prepared with the use of competency questions.

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Acknowledgments

The work was partially supported by European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 316097 [ENGINE] and by the National Science Centre, the decision no. DEC-2013/09/B/ST6/02317.

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Authors and Affiliations

  1. West Pomeranian University of Technology, Żołnierska 49, 71-210, Szczecin, Poland

    Jarosław Wątróbski & Jarosław Jankowski

  2. Department of Computational Intelligence, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Jarosław Jankowski

Authors
  1. Jarosław Wątróbski
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  2. Jarosław Jankowski
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Correspondence to Jarosław Jankowski .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

  3. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

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Wątróbski, J., Jankowski, J. (2016). An Ontology-Based Knowledge Representation of MCDA Methods. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_6

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  • DOI: https://doi.org/10.1007/978-3-662-49381-6_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49380-9

  • Online ISBN: 978-3-662-49381-6

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