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Contextual Hierarchy Driven Ontology Learning

Contextual Hierarchy Driven Ontology Learning

Lobna Karoui
Copyright: © 2009 |Pages: 22
ISBN13: 9781605660288|ISBN10: 1605660280|ISBN13 Softcover: 9781616925208|EISBN13: 9781605660295
DOI: 10.4018/978-1-60566-028-8.ch001
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MLA

Karoui, Lobna. "Contextual Hierarchy Driven Ontology Learning." The Semantic Web for Knowledge and Data Management, edited by Zongmin Ma and Huaiqing Wang, IGI Global, 2009, pp. 1-22. https://doi.org/10.4018/978-1-60566-028-8.ch001

APA

Karoui, L. (2009). Contextual Hierarchy Driven Ontology Learning. In Z. Ma & H. Wang (Eds.), The Semantic Web for Knowledge and Data Management (pp. 1-22). IGI Global. https://doi.org/10.4018/978-1-60566-028-8.ch001

Chicago

Karoui, Lobna. "Contextual Hierarchy Driven Ontology Learning." In The Semantic Web for Knowledge and Data Management, edited by Zongmin Ma and Huaiqing Wang, 1-22. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-028-8.ch001

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Abstract

Research in ontology learning had always separated between ontology building and evaluation tasks. Moreover, it had used for example a sentence, a syntactic structure or a set of words to establish the context of a word. However, this research avoids accounting for the structure of the document and the relation between the contexts. In our work, we combine these elements to generate an appropriate context definition for each word. Based on the context, we propose an unsupervised hierarchical clustering algorithm that, in the same time, extracts and evaluates the ontological concepts. Our results show that our concept discovery approach improves the conceptual quality and the relevance of the extracted ontological concepts, provides a support for the domain experts and facilitates the evaluation task for them.

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