Learning effective and robust knowledge for semantic query optimization

Abstract

This paper outlines a general learning approach to the knowledge acquisition problem of semantic query optimization. The results shows that the learned rules outperformed hand-coded rules and provided significant savings. For more detailed description of the approaches discussed in this paper, please refer to the author's doctoral dissertation [2]. Other references are available upon request.