¹Department of Computer Science and Technology, Jilin University, Jilin Changchun, China
²Department of Information, Changchun Taxation College, Jilin Changchun, China
³Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun, China

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Abstract—The key element in a Deep Web information fusion system is the data source modeling problem, which is the determinant technical factor of the whole system. The query interfaces provided by the Deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the lower generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of extracting attributes and semantic relationships from the interfaces utilizing Ontology is present in this paper, and WordNet is introduced as an Ontology instrument. The semantic relationships between semantic related attributes are evaluated by the WordNet. The meaningless attributes are instantiated by instance information embedded in the interfaces. A semantic matrix is generated and used to evaluate the semantic related groups in the specific domains. The expression ability of LAV is extended by the mapping and matching mechanism based on the semantic related groups. The experiment is carried out on the famous dataset, and the results show the efficiency of Ontology extended LAV of building mappings between local schemas and mediator schema.

Index Terms—Deep Web, information fusion, query interface, local as view, Ontology, WordNet.

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Cite: Liang Hao, Zuo Wan-Li, Ren Fei, "Describing the Semantic Relation of the Deep Web Query Interfaces Using Ontology Extended LAV," Journal of Software vol. 5, no. 1, pp. 89-98, 2010.