Deriving and Maintaining Rules in an Intelligent DBMS (Computer and Information Science)

在智能 DBMS 中导出和维护规则（计算机和信息科学）

• 批准号: 8710137
• 负责人: Edward Sciore
• 金额: $ 30.79万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-08-15 至 1990-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8710137&HistoricalAwards=false
• 关键词: Deriving; Maintaining; Rules; Intelligent; DBMS

This research investigates the automatic generation of inference rules to support intelligent data processing. For example, in knowledge-based systems, production rules encode knowledge used for expert reasoning. In database systems, inference rules encode integrity constraints used for semantic query optimization. Such rule-based systems now depend on human experts to supply the rules. This proposal focuses on a database application, developing a semantic query optimization system that automatically derives and maintains rules, based on database usage patterns and changes to the database state. The automatic derivation of rules is a promising self-adaptive database optimization technique that combines areas of research from both database theory and artificial intelligence. The importance of this research is that it will lead to improvements in the performance of many kinds of rule-based computer programs. System-derived rules can be more flexible and efficient than a set developed by a human expert. In addition, the criteria developed for automatic evaluation of various rule sets may be of use to human experts as well.

本研究探讨自动生成的 推理规则，以支持智能数据处理。为 例如，在基于知识的系统中，产生式规则编码 用于专家推理的知识。在数据库系统中， 推理规则编码用于语义的完整性约束 查询优化这种基于规则的系统现在依赖于人类 专家提供规则。本提案侧重于数据库 应用，开发了一个语义查询优化系统， 根据数据库自动推导和维护规则 使用模式和对数据库状态的更改。自动 规则推导是一种很有前途的自适应数据库 优化技术，结合了两个研究领域 数据库理论和人工智能。 这项研究的重要性在于它将导致 许多基于规则的 计算机程序。系统派生的规则可以更加灵活， 比人类专家开发的一套更有效。 此外，本发明还提供了一种方法， 为自动评估各种规则而开发标准 集合对于人类专家也是有用的。