RDF/XML has been widely recognized as the standard for annotating online Web documents and for transforming the HTML Web to the so called Semantic Web. In order to enable widespread usability for the Semantic Web there is a need to bootstrap large, rich and up-todate domain ontologies that organize most relevant concepts, their relationships and instances. In this paper, we present automated techiques for bootstrapping and populating specialized domain ontologies by organizing and mining a set of relevant Web sites provided by the user. We develop algorithms that detect and utilize HTML regularities in the Web documents to turn them into hierarchical semantic structures encoded as XML. Next, we present tree-mining algorithms that identify key domain concepts and their taxonomical relationships. We also extract semistructed concept instances annotated with their labels whenever they are available. Experimental evaluation for the News and Hotels domain indicates that our algorithms can bootstrap and populate domain specific ontologies with high precision and recall.

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In this paper, we present automated techniques for bootstrapping and populating specialized domain ontologies by organizing and mining a set of relevant overlapping Web sites provided by the user. We develop algorithms that detect and utilize HTML regularities in the Web documents to turn them into hierarchical semantic structures encoded as XML. Next, we present tree-mining algorithms that identify key domain concepts and their taxonomical relationships. We also extract semi-structured concept instances annotated with their labels whenever they are available. Experimental evaluation for the News, Travel, and Shopping domains indicates that our algorithms can bootstrap and populate domain specific ontologies with high precision and recall.