Rule Management in Expert Database Systems
研究专家数据库系统中基于关系数据连接条件的规则处理策略，提出辅助结构并开发处理框架，通过随机模型推导成本函数，性能评估表明方法有效。
Expert database systems combine database and expert systems technologies to support the effective management of both rules and data. This paper studies rule processing strategies in expert database systems involving rules that are conditional on joins of relational data. Auxiliary constructs for processing join rules are proposed, and a framework of join rule processing strategies is developed. Cost functions of several strategies are derived based on a stochastic model that characterizes the arrival processes of transactions and queries to the database. Performance evaluation shows that the proposed data constructs and strategies provide an effective method for processing rules.