CAREER: Enabling and Supporting Collaborative Knowledge Building Through Incremental Formalization

职业：通过渐进形式化实现和支持协作知识构建

• 批准号: 9734167
• 负责人: Frank Shipman
• 金额: $ 30万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-05-15 至 2003-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9734167&HistoricalAwards=false
• 关键词: CAREER; Enabling; Supporting; Collaborative; Knowledge

Traditionally, building knowledge-based systems has been a process involving professional knowledge engineers. While this process works for well-defined tasks in limited domains, it is too expensive for domains where the representation must change frequently and is not feasible for problems where experts' understanding of the domain and task changes during the course of problem solving. The alternative approach investigated in this project is one of "incremental formalization." This approach allows users to initially enter their understanding of their domain, task, and solutions in less formal representations and provides computer support for the gradual formalization of this knowledge. The project includes: (1) designing knowledge representations and interfaces for capturing emergent understandings and enabling incremental formalization, (2) developing mechanisms for recognizing implicit structure within informally represented information, (3) investigating interfaces for suggesting formalizations, uses of automated formalization, and trade-offs between suggesting and automating formalization, (4) creating tools which aid the development of shared languages and support collaborative knowledge-building tasks, and (5) improving understanding of knowledge-building processes and the relative merits of prototypes through observations of individual and collaborative tasks requiring domain modeling. http://www.csdl.tamu.edu/CKBE/

传统上，构建基于知识的系统是一个涉及专业知识工程师的过程。 虽然这一过程适用于有限领域中定义明确的任务，但对于表示必须经常改变的领域来说成本太高，并且对于专家对领域和任务的理解在解决问题的过程中发生变化的问题来说不可行。 在这个项目中研究的另一种方法是“增量形式化”。“这种方法允许用户最初以不太正式的表示形式输入他们对自己的领域、任务和解决方案的理解，并为这种知识的逐步形式化提供计算机支持。 该项目包括：（1）设计知识表示和接口，用于捕获紧急理解并实现增量形式化，（2）开发用于识别非正式表示的信息中的隐式结构的机制，（3）研究用于建议形式化的接口，自动形式化的使用，以及建议和自动形式化之间的权衡，（4）创建工具，帮助开发共享语言和支持协作知识构建任务，（5）通过观察需要领域建模的个人和协作任务，提高对知识构建过程和原型相对优点的理解。 http://www.csdl.tamu.edu/CKBE/