Cascading top-k keyword search over relational databases

Keyword search over relational databases has recently received significant attention. Many solutions and prototypes have been developed. However, due to large memory consumption requirements and unpredictable running time, most of them cannot be applied directly to situations where memory is limited and quick response is required, such as when performing keyword search over databases in mobile devices as part of the OLAP funtionalities. In this paper, we attack the keyword search problem from a new perspective, and propose a cascading top-k keyword search algorithm, which generates supernodes in each step of search instead of computing the Steiner trees as done in many existing approaches. This new algorithm consumes less memory and significantly reduces the response time. Experiments show that the method can achieve high search efficiency compared with the state-of-the-art approaches.