NYI: Design of Knowledge-Base Systems from Reusable components

NYI：利用可重用组件设计知识库系统

• 批准号: 9257578
• 负责人: Mark Musen
• 金额: $ 31.25万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-09-01 至 1999-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9257578&HistoricalAwards=false
• 关键词: NYI; Design; Knowledge; Base; Systems

The construction of knowledge-based systems is extremely labor-intensive. Unfortunately, current tools for building knowledge-based systems do not allow developers to take significant advantage of previous knowledge bases when building new systems. The research supported by this award involves design of a novel architecture for the construction of knowledge-based systems. The architecture allows system builders either to select an existing problem-solving method from a library, or to construct a new problem-solving method from a set of predefined building blocks. The developer then maps the data requirements of the problem-solving method to elements of reusable domain ontologies that define models of particular application areas. Both the domain ontologies and the problem-solving methods that are used to build knowledge-based systems are stored in libraries that future developers can access when implementing new applications. The research thus addresses strategies to index and retrieve problem-solving methods and domain ontologies, and to integrate these components within new problem-solving frameworks. The research will allow construction of new classes of tools for building knowledge-based systems, and will define an infrastructure that supports the reuse of knowledge-base components at increasingly high levels of abstraction. //

基于知识的系统的构建是极其劳动密集型的。 不幸的是，当前用于构建基于知识的系统的工具不允许开发人员在构建新系统时充分利用以前的知识库。 该奖项支持的研究涉及设计一种用于构建基于知识的系统的新颖架构。 该架构允许系统构建者从库中选择现有的问题解决方法，或者从一组预定义的构建块构建新的问题解决方法。 然后，开发人员将问题解决方法的数据需求映射到定义特定应用领域模型的可重用领域本体的元素。 用于构建基于知识的系统的领域本体和解决问题的方法都存储在未来开发人员在实现新应用程序时可以访问的库中。 因此，该研究提出了索引和检索问题解决方法和领域本体的策略，并将这些组件集成到新的问题解决框架中。 该研究将允许构建用于构建基于知识的系统的新型工具，并将定义一个支持在越来越高的抽象级别上重用知识库组件的基础设施。 //