Knowledge attributes: fuzzy application of temporal constraints in active expert database systems

Abstract

In active expert databases, current methodologies distinguish between the active execution of knowledge and the management of data. This distinction is extended to attributes, so that attributes also reflect both knowledge and data. The objective is to make the expert system more knowledgeable of, and responsive to, its own execution characteristics. Active databases are discussed with particular focus being given to execution determinism, basic principles of fuzzy logic and temporal issues, and various potential knowledge attributes that capture temporal execution and usage characteristics. The fuzzy interpretation of those characteristics in constraining the activity behind an active expert database system is discussed.<>