Ontology Instance-based Attributes Extracting for Deep Web
Fengling He · Journal of Chinese Computer Systems · 2009
The Deep Web is behi-nd the Surface Web and more information is hidden in it.The search engines and the web crawlers can not access the Deep Web directly.The only and workable way to access the hidden database is through query interface.Automatic extracting attributes from the query interface and translating a query is a solvable way for addressing the current limitations in accessing Deep Web data sources.The query interface provides semantic constraints,some attributes are co-occurred and the others are exclusive sometimes.To generate a valid query,we have to reconcile the key attributes and semantic relation between them.We design a framework to automatically extract the attributes from the query interface taking full advantage of instance information and use the WordNet as a kind of ontology technique to enrich the attributes embedded in the semantic query interface.Each attribute is extended into a candidate attribute set in the form of a hierarchy tree.We carry out our experiments in the real-world domain.The results of the experiments showed the validation of query translation framework.