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Assessing Ontology Alignments on the Level of Instances

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Computational Collective Intelligence (ICCCI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12876))

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Abstract

Metrics, such as Precision and Recall, are used to evaluate ontologies at both the design and application stages. The aim of the paper is to introduce two metrics that assess ontology alignments at the instance level, which can be used by people interested in ontology integration. These metrics allow to select the best mapping from existing ones. The usefulness of the metrics has been confirmed by their practical and experimental validation.

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Authors and Affiliations

  1. Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Bogumiła Hnatkowska, Adrianna Kozierkiewicz & Marcin Pietranik

  2. Faculty of Information Technology, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

    Hai Bang Truong

Authors
  1. Bogumiła Hnatkowska
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  2. Adrianna Kozierkiewicz
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  3. Marcin Pietranik
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  4. Hai Bang Truong
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Corresponding author

Correspondence to Marcin Pietranik .

Editor information

Editors and Affiliations

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

    Ngoc Thanh Nguyen

  2. Democritus University of Thrace, Kimmeria, Xanthi, Greece

    Lazaros Iliadis

  3. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

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

    Bogdan Trawiński

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Hnatkowska, B., Kozierkiewicz, A., Pietranik, M., Truong, H.B. (2021). Assessing Ontology Alignments on the Level of Instances. In: Nguyen, N.T., Iliadis, L., Maglogiannis, I., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2021. Lecture Notes in Computer Science(), vol 12876. Springer, Cham. https://doi.org/10.1007/978-3-030-88081-1_4

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  • DOI: https://doi.org/10.1007/978-3-030-88081-1_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-88080-4

  • Online ISBN: 978-3-030-88081-1

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