Reexamining database keyword search: Beyond performance

Abstract

As an active research field, database keyword search (KWS) has put much emphasis on the performance issues, due to its high computational cost. However, a closer examination on KWS reveals other interesting aspects worth noting. In this paper, we examine KWS from a broader perspective, particularly from its relationship with data mining. Freed from syntax-related considerations, KWS users now have better opportunities to explore the data in the way as they wish, and such exploration may reveal useful hindsight for what to be done in data mining. Recently we have conducted our KWS research from this unique perspective. We propose a software environment which offers a dual-mode approach to explore KWS: the database mode allows the implementation of database KWS directly by incorporating various KWS algorithms, while the XML mode converts the database contents to an XML document on which KWS is conducted. The dual mode approach not only has the potential of achieving integrated KWS on both structured and semistructured data, but also facilitates query relaxation by incorporating ontologies in the XML mode. The software environment still allows us to observe performance related issues of KWS; but more importantly, it offers a freehand approach for users to explore the data, thus has the potential of aiding data mining. Component design and experimental studies are described.