摘要
针对目前人工建立对象知识库的局限性 ,提供了一种基于样本利用、模式识别、形式文法和改进结构建模方法的面向对象知识库的建库新技术 ,它直接从客观世界提取样本知识 ,经过人工神经网络机制进行学习 ;然后通过语意理解器的识别从而达到提高知识确定性、减小信息熵的目的 ;
In consideration of the limit of object oriented knowledge database building process by individuals. A set of technology is layouted to dispose this problem, using sample application, model recognition, formal grammar, and structural modeling methods. This set of technology can acquire sample knowledge form environment and learn it through ANN, interpreting the pending knowledge, and using structural modeling methods to get object oriented derisive system.
出处
《华中理工大学学报》
CSCD
北大核心
2000年第1期26-28,共3页
Journal of Huazhong University of Science and Technology
基金
国家自然科学基金资助项目 !( 7950 0 0 0 7)
关键词
人工智能
面向对象技术
样本建模
知识库
artificial intelligence
neural network
object oriented technology
sample
