Ontology Mining for Personalized Web Information Gathering
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Abstract
It is well accepted that ontology is useful for personalized Web information gathering. However, it is challenging to use semantic relations of “kind-ofâ€, “part-ofâ€, and “related-to†and synthesize commonsense and expert knowledge in a single computational model. In this paper, a personalized ontology model is proposed attempting to answer this challenge. A two-dimensional (Exhaustively and Specificity) method is also presented to quantitatively analyze these semantic relations in a single framework. The proposals are successfully evaluated by applying the model to a Web information gathering system. The model is a significant contribution to personalized ontology engineering and concept-based Web information gathering in Web Intelligence.
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Keywords: kind-of, mining, ontology and clustering
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