液氧煤油发动机知识分类模型及自动分类标记平台设计  

Design of Knowledge Classification Model Engine and Automatic Classification Marking Platform of Liquid Oxygen Kerosene

作　　者：许婷[1] 董秦刚 XU Ting;DONG Qin′gang(Xi′an Aerospace Propulsion Institute,Xi′an 710100,China)

机构地区：[1]西安航天动力研究所,西安710100

出　　处：《西安航空学院学报》2023年第3期67-76,共10页Journal of Xi’an Aeronautical Institute

摘　　要：采用自然语言处理技术提取文档特征,运用规则知识库与神经网络模型,在对液氧煤油发动机技术原有文件资料人工知识分类标记的基础上,实现新增技术成果所属的专业分类、知识分类、专业技术分类、关键技术分类等维度的自动分类标记,形成智能化、常态化知识资源自动积累机制,能够保障液氧煤油发动机文件资料的分类积累,为设计创新提供借鉴和参考。Natural language processing technology is used to extract document features,and rule knowledge base and neural network model are used to realize automatic classification and labeling of new technical achievements in terms of professional classification,knowledge classification,professional technology classification and key technology classification on the basis of manual knowledge classification and labeling of original documents and materials of liquid oxygen kerosene engine technology.The formation of intelligent and normalized automatic accumulation mechanism of knowledge resources can ensure the classification and accumulation of liquid oxygen and kerosene engine documents,and provide useful reference for design innovation.

关 键 词：液氧煤油发动机 自然语言处理 分类模型 神经网络 分类标记 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]