Ontology augmentation: combining semantic web and text resources

Miriam Fernandez, Vanessa Lopez, Enrico Motta, Ziqi Zhang, Victoria Uren

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

This work investigates the process of selecting, extracting and reorganizing content from Semantic Web information sources, to produce an ontology meeting the specifications of a particular domain and/or task. The process is combined with traditional text-based ontology learning methods to achieve tolerance to knowledge incompleteness. The paper describes the approach and presents experiments in which an ontology was built for a diet evaluation task. Although the example presented concerns the specific case of building a nutritional ontology, the methods employed are domain independent and transferrable to other use cases.
Original languageEnglish
Title of host publicationProceeding : K-CAP '11
Subtitle of host publicationproceedings of the sixth international conference on knowledge capture
Place of PublicationNew York, NY (US)
PublisherACM
Pages9-16
Number of pages8
ISBN (Print)978-1-4503-0396-5
DOIs
Publication statusPublished - 2011
Event6th International Conference on Knowledge Capture - Alberta, Canada
Duration: 25 Jun 201129 Jun 2011

Conference

Conference6th International Conference on Knowledge Capture
Abbreviated titleKCAP 2011
CountryCanada
CityAlberta
Period25/06/1129/06/11

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  • Cite this

    Fernandez, M., Lopez, V., Motta, E., Zhang, Z., & Uren, V. (2011). Ontology augmentation: combining semantic web and text resources. In Proceeding : K-CAP '11: proceedings of the sixth international conference on knowledge capture (pp. 9-16). ACM. https://doi.org/10.1145/1999676.1999680