摘要
针对5G技术,提出一种基于文本挖掘的研究热点识别的新方法。从web of science数据库中检索2013至2018年间以5G技术为主题的11 429篇科研论文,基于文本关联规则挖掘构建关键词网络,以信息熵和组合力作为指标对论文的高频关键词进行聚类分析,在此基础上识别出5G领域的三类热点技术。
Aiming at 5G technology,this paper proposes a novel method to identify hot research topics based on text mining.We retrieved 11429 research papers with 5 G technology as the subject between 2013 to 2018 from the Web of Science database,and constructed a keyword network based on text association rules mining.Then we used information entropy and combination force as indicators to cluster high-frequency keywords.Three hot research topics in the field of 5 G are identified on the basis of clustering results.
作者
李晶
罗泰晔
Li Jing;Luo Taiye(School of Management,Xinhua College,Sun Yat-sen University,Guangzhou 510520,China;School of Business Administration,South China University of Technology,Guangzhou 510640,China)
出处
《科技管理研究》
CSSCI
北大核心
2020年第19期153-158,共6页
Science and Technology Management Research
基金
广东省软科学重大项目“科技革命与技术预见智库建设”(2016B070702001)。
关键词
研究热点
关联规则
聚类
信息熵
5G
hot research topics
association rules
clustering
information entropy
5G
