SPHINX: Schema integration by example
The Internet has instigated a critical need for automated tools that facilitate integrating countless databases. Since nontechnical end users are often the ultimate repositories of the domain information required to distinguish differences in data types, an effective solution must integrate simple GUI based data browsing tools and automatic mapping methods that eliminate the requirement for a technical user to supervise the process. We develop a metamodel of data integration as the basis for absorbing feedback from an end user. The schema integration algorithm draws examples from the data and learns integrating view definitions by asking a user simple yes or no questions. The metamodel enables a search mechanism that is guaranteed to converge to a correct integrating view definition without the user having to know a view definition language such as SQL or SchemaSQL, or even having to inspect the final view definition. We show how data catalog statistics, normally used to optimize queries, can be exploited to parameterize the search heuristics and improve the convergence of the learning algorithm.
schema integration schema mapping query discovery active learning version spaces