Fernandez, Miriam; Zhang, Ziqui ; Lopez, Vanessa; Uren, Victoria and Motta, Enrico
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|DOI (Digital Object Identifier) Link:||http://doi.org/10.1145/1999676.1999680|
|Google Scholar:||Look up in Google Scholar|
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.
|Item Type:||Conference Item|
|Copyright Holders:||2011 ACM|
|Keywords:||knowledge acquisition; knowledge capture; ontology learning; ontology augmentation; semantic web|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Kay Dave|
|Date Deposited:||17 Aug 2011 08:12|
|Last Modified:||06 Aug 2016 17:25|
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