Mapping Mechanism Based on Ontology Extended Semantic Related Groups

Query interfaces provided by the Deep Web are 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. To address the problem, an Ontology extended semantic related group algorithm is presented. The algorithm is to extract attributes using Ontology technique, and the semantic distance between any pairs of candidate attributes is evaluated by WordNet. A semantic matrix is generated and a reverse backtracking algorithm is used to find semantic related groups of attributes. A matching mechanism is constructed on the semantic related groups, by which the expression ability of LAV is extended. The validation and effectiveness were tested based on experiments.