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[ "赵东明(1984- ),男,博士,中国移动通信集团天津有限公司正高级工程师、AI实验室负责人,主要研究方向为知识图谱、情感计算及认知网络" ]
网络出版日期:2022-08,
纸质出版日期:2022-08-20
移动端阅览
赵东明. 电信运营商知识图谱技术体系研究及应用实践[J]. 电信科学, 2022,38(8):151-162.
Dongming ZHAO. Research and application practice of knowledge graph technology system for telecom-operators[J]. Telecommunications science, 2022, 38(8): 151-162.
赵东明. 电信运营商知识图谱技术体系研究及应用实践[J]. 电信科学, 2022,38(8):151-162. DOI: 10.11959/j.issn.1000-0801.2022145.
Dongming ZHAO. Research and application practice of knowledge graph technology system for telecom-operators[J]. Telecommunications science, 2022, 38(8): 151-162. DOI: 10.11959/j.issn.1000-0801.2022145.
摘 要:知识图谱在电信运营商业务及运维场景的知识搜索、工单处理、智能服务、故障分析等领域发挥着重要作用,以中国移动业务运营场景为依托,体系化地研究了知识图谱技术体系,基于应用场景、服务对象可分为问答检索类知识图谱、工单分析类知识图谱、系统运维类知识图谱和业务运营类知识图谱,并介绍其技术架构、业务架构及构建方法,引出知识图谱演进与发展的规划目标。
Knowledge graph plays an important role in knowledge search
work order processing
intelligent service
fault analysis and other fields of China Mobile business and maintenance scenario.The knowledge graph technology system of China Mobile was systematically studied.Based on application scenarios and service objects
it can be divided into question & answer retrieval knowledge graph
work-order analysis knowledge graph
system operation and maintenance knowledge graph and business operation knowledge graph.The technical architecture
business architecture and construction methods were introduced
and the planning goal of the evolution and development of knowledge graph was ultimately leaded.
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NIU H R , HE H T , FENG J Z , et al . Knowledge graph completion based on GCN of multi-information fusion and high- dimensional structure analysis weight [J ] . Chinese Journal of Electronics , 2022 , 31 ( 2 ): 387 - 396 .
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WANG W G , XU Y L , DU C H , et al . Data set and evaluation of automated construction of financial knowledge graph [J ] . Data Intelligence , 2021 , 3 ( 3 ): 418 - 443 .
CHEN Y . Constructing bug knowledge graph as a service for bug search [J ] . International Journal of Software Engineering and Knowledge Engineering , 2021 , 31 ( 1 ): 81 - 98 .
PU F , ZHANG Z , FENG Y , et al . Learning context-based embeddings for knowledge graph completion [J ] . Journal of data and Information Science , 2022 , 7 ( 2 ): 23 - 29 .
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