Abstract

An important and difficult problem in Knowledge Management is how to efficiently retrieve information from distributed, heterogeneous multidatabase systems. This project addresses this problem by bringing to bear a richer set of knowledge about databases to optimize multidatabases queries. The idea is to use semantic knowledge of the contents of databases to reformulate queries into equivalent yet less expensive ones. Using this knowledge, the potential cost reduction is significantly more than can be derived from convention query optimization alone. Since the semantic knowledge required can be learned from any database, this approach is applicable to other Knowledge-intensive systems.***

Date

January 1, 1970

Authors

Craig A Knoblock

Journal

NSF Award Number 9313993. Directorate for Computer and Information Science and Engineering

Volume

93

Issue

9313993

Pages

13993