We present a new application for keyword search within relational databases, which uses a novel algorithm to solve the join discovery problem by finding Memex-like trails through the graph of foreign key dependencies. It differs from previous efforts in the algorithms used, in the presentation mechanism and in the use of primary-key only database queries at query-time to maintain a fast response for users. We present examples using the DBLP data set.
DBXplorer @cite_3 was developed by Microsoft Research, and like BANKS and Mragyati, it uses join trees to compute an SQL statement to access the data. The algorithm to compute these differs, as does the implementation, which was developed for Microsoft's IIS and SQL Server, the others being implemented in Java. DbSurfer does not require access to the database to discover the trails, only to display the data when user clicks on a link in that trail.
@cite_3
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Internet search engines have popularized the keyword-based search paradigm. While traditional database management systems offer powerful query languages, they do not allow keyword-based search. In this paper, we discuss DBXplorer, a system that enables keyword-based searches in relational databases. DBXplorer has been implemented using a commercial relational database and Web server and allows users to interact via a browser front-end. We outline the challenges and discuss the implementation of our system, including results of extensive experimental evaluation.