摘要
模糊概念图作为一种模糊不确定知识表示方法,已经引起人工智能学者的广泛关注.在MORTON提出的模糊概念图表示方法中,用模糊度表示概念的不确定性具有一定的局限性.为了克服这种局限性,将模糊数学理论同传统模糊概念图相结合,从模糊不确定知识表示方面对概念图进行研究,采用模糊集表示模糊概念图中概念节点和关系节点的模糊度,提出一种改进的模糊概念图知识表示方法,设计了相应的存储结构,并研究了模糊概念图的匹配操作.改进的模糊概念图已经应用于主观题自动阅卷方法中,正确率较高.
As a knowledge representation of fuzzy uncertainty,fuzzy conceptual graphs have attracted wide attention from scholars of artificial intelligence. In MORTON＇s representation of fuzzy conceptual graphs,fussiness has certain limitation. To overcome this limitation,we combine fuzzy mathematics theory with traditional fuzzy conceptual graph and study fuzzy conceptual graph in terms of fuzzy uncertain knowledge representation. An improved representation of fuzzy conceptual graph is presented in this paper. Fuzzy set is used to represent the fuzziness of concepts and conceptual relations in fuzzy conceptual graph. The storage structure of fuzzy conceptual graph is designed according to this representation,and the matching operation rules of fuzzy conceptual graph are established. Improved fuzzy conceptual graph has been applied to methods of automatic checking over subjective examination,the accuracy is high.
出处
《微电子学与计算机》
CSCD
北大核心
2010年第11期25-29,共5页
Microelectronics & Computer
基金
国家自然科学基金项目(60673170)
陕西省教育厅自然科学基金(08JK318)
西安建筑科技大学人才基金项目(RC0618)
关键词
模糊概念图
模糊集合
知识表示
fuzzy conceptual graph
fuzzy set
knowledge representation
