出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Today, the notion of Semantic Web has emerged as a prominent solution to the problem oforganizing the immense information provided by World Wide Web, and its focus on supportinga better co-operation between humans and machines is noteworthy. Ontology forms the majorcomponent of Semantic Web in its realization. However, manual method of ontologyconstruction is time-consuming, costly, error-prone and inflexible to change and in addition, itrequires a complete participation of knowledge engineer or domain expert. To address thisissue, researchers hoped that a semi-automatic or automatic process would result in faster andbetter ontology construction and enrichment. Ontology learning has become recently a majorarea of research, whose goal is to facilitate construction of ontologies, which reduces the effortin developing ontology for a new domain. However, there are few research studies that attemptto construct ontology from semi-structured Web pages. In this paper, we present a completeframework for ontology learning that facilitates the semi-automation of constructing andenriching web site ontology from semi structured Web pages. The proposed framework employsWeb Content Mining and Web Usage mining in extracting conceptual relationship from Web.The main idea behind this concept was to incorporate the web author's ideas as well as webusers’ intentions in the ontology development and its evolution.
关键词：Ontology Learning; Web Mining; Web Content Mining; Web Usage Mining; Ontology;Evaluation
