Fernandez, Miriam; Zhang, Ziqui ; Lopez, Vanessa; Uren, Victoria and Motta, Enrico
(2011).
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(Version of Record)
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| DOI (Digital Object Identifier) Link: | https://doi.org/10.1145/1999676.1999680 |
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| Google Scholar: | Look up in Google Scholar |
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.
| Item Type: | Conference or Workshop Item |
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| Copyright Holders: | 2011 ACM |
| Keywords: | knowledge acquisition; knowledge capture; ontology learning; ontology augmentation; semantic web |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Research Group: | Centre for Research in Computing (CRC) |
| Related URLs: | |
| Item ID: | 29125 |
| Depositing User: | Kay Dave |
| Date Deposited: | 17 Aug 2011 08:12 |
| Last Modified: | 20 Dec 2017 16:52 |
| URI: | http://oro.open.ac.uk/id/eprint/29125 |
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