Ontology augmentation: combining semantic web and text resources

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

Research output: Chapter in Book/Published conference outputConference publication


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)
Number of pages8
ISBN (Print)978-1-4503-0396-5
Publication statusPublished - 2011
Event6th International Conference on Knowledge Capture - Alberta, Canada
Duration: 25 Jun 201129 Jun 2011


Conference6th International Conference on Knowledge Capture
Abbreviated titleKCAP 2011


Dive into the research topics of 'Ontology augmentation: combining semantic web and text resources'. Together they form a unique fingerprint.

Cite this