基于知识图谱的学术期刊稿源优化数据可视化分析  

Visualization analysis of optimization of academic journal manuscript source

作　　者：黄颖 杨蒿[1,2] 汪道友[2] HUANG Ying;YANG Hao;WANG Daoyou(Editorial Office of Matter and Radiation at Extreme Conditions(English),China Academy of Engineering Physics,Mianyang 621999,P.R.China;Editorial office of High Power Laser and Particle Beams,Science and Technology Information Center,China Academy of Engineering Physics,Mianyang 621999,P.R.China)

机构地区：[1]中国工程物理研究院科技信息中心《极端条件下的物质与辐射(英文)》编辑部,四川绵阳621999 [2]中国工程物理研究院科技信息中心《强激光与粒子束》编辑部,四川绵阳621999

出　　处：《学术出版与传播》2023年第1期134-141,共8页SCHOLARLY PUBLISHING AND COMMUNICATIONS

摘　　要：稿源质量是学术期刊的核心竞争力和学术影响力的重要体现。利用知识图谱和聚类可视化分析方法,充分挖掘期刊自身论文、作者和读者等核心学术资源,形成高效、精准的稿源优化策略,为学术期刊选题策划、组稿约稿提供重要的指导和依据。The quality of manuscript sources is an important affect of the core competitiveness and academic influence of academic journals.By utilizing knowledge graph and clustering visualization analysis methods,the core academic resources of journals,such as articles,authors,and readers,can be fully explored.This enables the development of efficient and precise strategies for optimizing manuscript sources.It also provides important guidance and basis for academic journal topic pluanning,manuscript selection,and commissioning.

关 键 词：学术期刊 稿源 选题策划 组稿 可视化分析 知识图谱 

分 类 号：G232[文化科学]