面向研究性项目文档的知识画像模型  

Knowledge Portrait Model for Research Project Documents

作　　者：武迪 艾中良[1] 刘忠麟[1] 李常宝[1] WU Di;AI Zhong-liang;LIU Zhong-lin;LI Chang-bao(North China Institute of Computing Technology,Beijing 100083,China)

机构地区：[1]华北计算技术研究所

出　　处：《计算机与现代化》2020年第2期60-64,69,共6页Computer and Modernization

摘　　要：为提高科研活动产生的研究性项目文档的知识要点的精准智能识别和检索能力,通过分析文档行文结构,提出建立文档知识画像的方法。设计精准贴合研究性项目文档结构的多层次的知识画像,自动识别文档知识要点,并按语义段落多粒度提取知识要点。采用知识表达准确率对模型的知识提取精确度进行检验,实验结果表明模型比传统方法对文档知识描述更准确,可在实际工作中使用。Aiming to improve the ability of accurate and intelligent identification of the knowledge points of the research project documents produced by research activities,we analyzed the document structure and proposed a method for establishing document knowledge portrait.A multi-level knowledge portrait fitting the structure of documents is designed.It identified the key points of the document knowledge automatically and extracted the knowledge points according to the multi-granularity of the semantic paragraph.The accuracy of knowledge extraction is used to test the accuracy of the model.The experimental results show that the model is more accurate than the traditional method for document knowledge description and can be used in practical application.

关 键 词：研究性项目文档 知识画像 知识提取 文档描述模型 结构要素 

分 类 号：TP391.12[自动化与计算机技术—计算机应用技术]