A Metadata Search Approach with Branch and Bound Algorithm to Keyword Query in Relational Databases

Search engines on the Web have popularized the keyword-based search paradigm, while searching in databases users need to know a database schema and a query language. Keyword search techniques on the Web cannot directly be applied to databases because the data on the Internet and database are in different forms. So keyword search systems in relational databases have recently proposed. However existing systems limit type of keywords to database value terms, and generally assumed that answers are in instance level. Thus, this research aims to propose an effective approach for free-form keyword searching in databases which allows users to search either with database value terms, metadata terms or user terms. The metadata model accommodates these terms as well as underlying database semantics. Moreover, we present a branch and bound algorithm used for finding the optimal answer graphs. Our preliminary experiment results confirm precision of our approach.