摘要
传统的知识表示方法主要有产生式规则、框架等,这些方法的缺点是对数据的完整性要求严格,无法灵活的表示人类知识.通过对政府环境下的知识元素进行分析和分类,引入了一种新的知识表示方法———三值逻辑神经网络.它的语义和符号表示的双重特性赋予了它强大的知识表示能力,不仅能表示格式化的文档知识,还能表示常规的、主观的人类知识,而这两者在政府的日常工作中是并存的.
The conventional methods lack the flexibility and the ability to express human knowledge. By analyzing and categorizing the knowledge elements in the government context, a new model for knowledge representation - three valued neural logic network（Neulonet） is introduced. The duality of Neulonet rule （ semantic and numeric features） endow it with great expressive power. Its greatest merit in expressing government knowledge is the capability to represent subjective and regular human knowledge as well as formalized document knowledge, which often co - exist in the routine work of government.
出处
《哈尔滨理工大学学报》
CAS
2005年第4期125-128,共4页
Journal of Harbin University of Science and Technology
基金
黑龙江省自然科学基金资助项目(G2004-02)
关键词
政府知识管理
知识表示
三值逻辑神经网络
government knowledge management
knowledge representation
3 -vauled neural logic network
