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Article type: Other
Authors: Pivk, Aleksander
Affiliations: Jozef Stefan Institute, Department of Intelligent Systems, Jamova 39, Ljubljana, Slovenia E-mail: aleksander.pivk@ijs.si
Abstract: Turning the current Web into a Semantic Web requires automatic approaches for document annotation, since manual approaches will not scale in general. The focus of the thesis is on automatic transformation of arbitrary table-like structures into knowledge models, i.e., ontologies. The presented work is based on Hurst's table model and consists of a methodology, an accompanying implementation named TARTAR, and a thorough evaluation. The evaluation showed over 80% success rate of automatic transformation of tables into semantic representations and 100% accuracy in the task of query answering over the table contents.
Keywords: Ontology, ontology learning/generation, semantic Web, tabular structure, intelligent agents
Journal: AI Communications, vol. 19, no. 1, pp. 83-85, 2006
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