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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fang Tian Peilin Jiang Ren, F. |
| Copyright Year | 2009 |
| Abstract | This paper proposes an ontology learning system model based on the Web search engine and Protege-OWL API, which emphasizes iterative learning approach by the extracted instances. We discuss taxonomic and non-taxonomic relationship learning separately in ontology learning system, and investigate the importance of verb plus noun phrase learning for extraction of activity concepts in Chinese. We also propose an algorithm of relevance measurement for extracting relation instances by binary keywords based on co-occurrence statistics. Finally, we build a practical system of ontology learning through learning relation instances of the Chinese festival ontology, and test the effectiveness of our method. |
| Starting Page | 298 |
| Ending Page | 303 |
| File Size | 215408 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424438518 |
| DOI | 10.1109/ICIW.2009.50 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-24 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Ontology Loading OWL Taxonomy Relation Extraction Ontologies Data mining Learning systems Web and internet services Search engines Iterative algorithms Iterative methods Ontology Learning Web search |
| Content Type | Text |
| Resource Type | Article |
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