To Develop A Relational Data-Knowledge Base System
For Solving Decision Problems With Large Data
Department of Information Science,
National Chiao Tung University,
Hsinchu, Taiwan 30050,
Republic of China
This paper aims to develop a data-knowledge base system for solving decision problems which involve large amount of data under some straightforward decision rules. This data-knowledge base system can handle both data and knowledge processes. It is the expansion of relational database systems under the control of relational DBMS. Since the modularity between the rules in Production Systems is highly similar to that between the tuples in RDBMS, the same type of rules can be grouped as a relation. An "IF" statement within a rule is the key of the corresponding tuple. Consequently, by utilizing an RDBMS, the human knowledge and data files can be integrated and manipulated mutually. To compare the performance of this system with conventional artificial intelligence programs, a typical decision problem is programmed and operated by both dBASE III and Micro-Prolog. The study's findings suggest that this proposed system has faster executing speed for solving decision problems which have large arrays data and can represent its decision rules by normalized relations.