DATABASE KEYWORD SEARCH: BEYOND ITS CURRENT LANDSCAPE

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 that there are some other interesting aspects worth noting. In this paper, we examine KWS from a broader perspective, analyzing its profound implications. 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 understanding the hidden nature of the data, thus benefiting the exploitation on the use of the data. In particular, we examine the potential of KWS to data mining from the behavior mining perspective. This examination also leads us to a discussion of viewing KWS in the "web of life" context. We further discuss connections of KWS with other related concepts, including dataspace. Based on our findings and critical examination, we also provide a brief overview of an integrated environment which facilitates the interplay of KWS and data mining.