基于图论的产业网络知识图谱挖掘与构建  

Construction of industry knowledge graph based on graph theory

作　　者：李振军 刘祖军 王鹏 杨斌 李大中 郭钰 赵华 LI Zhenjun;LIU Zujun;WANG Peng;YANG Bin;LI Dazhong;GUO Yu;ZHAO Hua(Smart Steps Digital Technology Company Limited,Beijing 100000,China;China Unicom Research Institute,Beijing 100000,China;China Unicom Digital Technology Co.,Ltd.,Beijing 100000,China)

机构地区：[1]智慧足迹数据科技有限公司,北京100000 [2]中国联合网络通信有限公司研究院,北京100000 [3]联通数字科技有限公司,北京100000

出　　处：《大数据》2023年第6期174-183,共10页Big Data Research

摘　　要：我国是全球产业规模最大、产业覆盖最全的国家,但受多种因素的影响,发现产业链的堵点断点、识别卡点、寻找代替通路、全面优化产业链势在必行。从数据底座构建、核心知识图谱挖掘、兼容传统产业链知识3个方面,阐述了基于图论的产业网络知识图谱的构建过程,以实现产业优化升级与模拟仿真。分析了产业网络知识图谱的应用场景和优势,并给出了其在集成电路行业的应用案例。China has the largest industrial scale and the most abundant industry type among the world.However,due to the influence of many factors,it is necessary to discover the blocking and breakpoints of the industrial chain,identify the stuck points,find alternative channels,and comprehensively optimize the industry.Then,this article explained the construction process of the industry knowledge graph from three aspects:data base construction,core knowledge graph mining,and compatibility with traditional industry chain knowledge.Finally the application scenarios and advantages of industry knowledge graph was analyzed,and an application case was given in the integrated circuit industry.

关 键 词：图论 产业图谱 知识网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]