Cooperative and Reactive Agents for Information Systems

Abstract : Active database systems have received increasing interest from both research and industrial communities. However, trigger conditions in the active rules are often difficult to specify, especially as the complexity of the events and/or condition: increases. To remedy this problem, we propose an active database system that supports rules with conceptual terms, approximate operators, and complex events. The conceptual terms and approximate operators are user and context sensitive. By introducing these high-level constructs, we not only simplify the rule specification process, but also increase the rule expressiveness. Knowledge-based relaxation techniques are used for rule specification and relaxation. High-level concepts and approximate operators used in rules are first relaxed into low-level active rules by using a tree-type knowledge structure called Type Abstraction Hierarchy which can be generated automatically from the database using clustering algorithms. The low-level rules are decomposed into a set of database triggers, which are then submitted into commercial active relational databases for simple trigger-processing. Thus, our proposed high-level active database system supports complex event detection without modification of the underlying database systems. The proposed active database system with high-level rule processing and complex event detection has been implemented at UCLA. The system operates on top of commercial relational databases that demonstrate the feasibility of high-level rule processing and complex event detection.