Sharing work in keyword search over databases

An important means of allowing non-expert end-users to pose ad hoc queries — whether over single databases or data integration systems — is through keyword search. Given a set of keywords, the query processor finds matches across different tuples and tables. It computes and executes a set of relational sub-queries whose results are combined to produce the k highest ranking answers. Work on keyword search primarily focuses on single-database, single-query settings: each query is answered in isolation, despite possible overlap between queries posed by different users or at different times; and the number of relevant tables is assumed to be small, meaning that sub-queries can be processed without using cost-based methods to combine work. As we apply keyword search to support ad hoc data integration queries over scientific or other databases on the Web, we must reuse and combine computation. In this paper, we propose an architecture that continuously receives sets of ranked keyword ...

• Type: Journal
• Year: 2011
• Where: SIGMOD
• Authors: Marie Jacob, Zachary G. Ives
• Keywords: Data Integration Systems, Database, Database Management Systems, SIGMOD 2011, Synthetic Data Sets