On-the-Fly Constraint Mapping across Web Query Interfaces

Recently, the Web has been rapidly “deepened” with the prevalence of databases online and becomes an important frontier for data integration. On this deep Web, a significant amount of information can only be accessed as response to dynamically issued queries to the query interface of a back-end database, instead of by traversing static URL links. Such a query interface expresses a set of constraint templates, where each constraint template states how an attribute can be queried. To enable automatic query mediation among heterogenous deep Web sources, it is critical to automatically translate those constraints, which we name as constraint mapping. In particular, this paper aims at enabling on-the-fly constraint mapping, toward on-the-fly integration of Web databases, due to the the large scale and dynamic nature of the deep Web. Such on-the-fly query translation poses a significant new challenge on the generality and extensibility of the translation framework. Existing works pursue a per-source rule-driven framework and thus cannot satisfy such requirements. In contrast, we propose a generic type-based search-driven translation framework by considering the constraint mapping for each data type as a search problem. In particular, in this paper, we develop search algorithms for text and numeric types. Our experiments over real deep Web sources show that our approach is promising as a principle way to mediate queries for large scale integration.