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Phrase2Onto: A Tool to Support Ontology Extension
Linköping University, Swedish e-Science Research Centre, Sweden.
Linköping University, Swedish e-Science Research Centre, Sweden.
Linköping University, Swedish e-Science Research Centre, Sweden.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Building Engineering, Energy Systems and Sustainability Science, Energy Systems and Building Technology. Linköping University, Swedish e-Science Research Centre, Sweden.ORCID iD: 0000-0002-9084-0470
2023 (English)In: Procedia Computer Science, E-ISSN 1877-0509, Vol. 225, p. 1415-1424Article in journal (Refereed) Published
Abstract [en]

Due to importance of data FAIRness (Findable, Accessible, Interoperable, Reusable), ontologies as a means to make data FAIR have attracted more and more attention in different communities and are being used in semantically-enabled applications. However, to obtain good results while using ontologies in these applications, high quality ontologies are needed of which completeness is one of the important aspects. An ontology lacking information can lead to missing results. In this paper we present a tool, Phrase2Onto, that supports users in extending ontologies to make the ontologies more complete. It is particularly suited for ontology extension using a phrase-based topic model approach, but the tool can support any extension approach where a user needs to make decisions regarding the appropriateness of using phrases to define new concepts. We describe the functionality of the tool and a user study using Pizza Ontology. The user study showed a good usability of the system and high task completion. Further, we report on a real application where we extend the Materials Design Ontology.

Place, publisher, year, edition, pages
Elsevier , 2023. Vol. 225, p. 1415-1424
Keywords [en]
Ontology extension, Concept discovery, phrase-based topic model
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hig:diva-43754DOI: 10.1016/j.procs.2023.10.130Scopus ID: 2-s2.0-85183562852OAI: oai:DiVA.org:hig-43754DiVA, id: diva2:1834525
Conference
27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023, Athens, Greece, 6-8 September 2023
Funder
Swedish Research Council, 2018-04147Available from: 2024-02-05 Created: 2024-02-05 Last updated: 2024-02-05Bibliographically approved

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Lambrix, Patrick

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CiteExportLink to record
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Citation style
  • apa
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  • sv-SE
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