Proceedings of the VLDB Endowment · 2009 · 74 citations · 21 references
EngineeringMuch DataHierarchical ApproachSemantic Web DataSemantic WebText MiningWeb Query InterfacesNatural Language ProcessingInformation RetrievalData ScienceManagementData IntegrationSemi-structured DataQuery ExpansionData ManagementWeb EngineeringKnowledge DiscoveryAutomatic ExtractionComputer ScienceQuery AnalysisQuery OptimizationWeb ArchitectureTree StructureWeb Information SystemXml QueryingWeb SemanticsData ModelingWeb Source Integration
Much data in the Web is hidden behind Web query interfaces. In most cases the only means to "surface" the content of a Web database is by formulating complex queries on such interfaces. Applications such as Deep Web crawling and Web database integration require an automatic usage of these interfaces. Therefore, an important problem to be addressed is the automatic extraction of query interfaces into an appropriate model. We hypothesize the existence of a set of domain-independent "commonsense design rules" that guides the creation of Web query interfaces. These rules transform query interfaces into schema trees. In this paper we describe a Web query interface extraction algorithm, which combines HTML tokens and the geometric layout of these tokens within a Web page. Tokens are classified into several classes out of which the most significant ones are text tokens and field tokens. A tree structure is derived for text tokens using their geometric layout. Another tree structure is derived for the field tokens. The hierarchical representation of a query interface is obtained by iteratively merging these two trees. Thus, we convert the extraction problem into an integration problem. Our experiments show the promise of our algorithm: it outperforms the previous approaches on extracting query interfaces on about 6.5% in accuracy as evaluated over three corpora with more than 500 Deep Web interfaces from 15 different domains.
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