A Deep Web Query Generation Method Using Semantic Annotation

To solve the problem of Deep Web query generation automatically, this paper first proposes a query interface criterion of Deep Web called S-LAV, ascertaining predecessor and successor relations between controls and utilizing them in controls grouping, constructing RIT model with a corresponding algorithm description. Then, the process of controls grouping is divided into 2 phases: control pre-clustering based on heuristic rules and semantic annotation based on How Net, which aims to promote the precision and relativity of query word libraries. Finally, in order to build query word libraries, a method of query word libraries generation and a method of query word expanding using relative feedback are proposed. Experiment on a practical Deep Web site shows that the scale of query word libraries with a high relativity is reduced.