摘要
基于一个整合了主题建模、专利文本分析和主题强度演进的量化分析框架,通过复合检索式采集全球范围内智慧城市相关专利,应用主题建模和文本挖掘方法刻画智慧城市技术热点演进的知识图谱,并对潜在热点主题进行识别与讨论,从而进一步丰富基于专利文本数据进行技术热点分析的方法体系。
Based on a quantitative analysis framework that integrates topic modeling,patent text analysis and topic intensity evolution,this study collected patents related to smart cities around the world through composite retrieval,then applied topic modeling and text mining methods to depict the knowledge map of the evolution of technology hotspots on smart city,and then identified and discussed those potential hot topics.Therefore,this study could further enrich the method system of technical hot spot analysis based on patent text data.
作者
李牧南
赖华鹏
Li Munan;Lai Huapeng(School of Business Administration,South China University of Technology,Guangzhou 501641,China;Guangdong Provincial Key Laboratory of Innovative Methods and Decision Management System,Guangzhou 501641,China)
出处
《科技管理研究》
CSSCI
北大核心
2023年第9期132-139,共8页
Science and Technology Management Research
基金
国家自然科学基金面上项目“基于多源数据融合与机器学习的新兴技术风险挖掘研究”(72074081)
广东省软科学研究计划重点项目“智慧城市和工业互联网前沿领域的技术预测研究”(2019B101001002)。
关键词
智慧城市
技术热点
专利挖掘
主题建模
smart city
technical hotspot
patent mining
topic modeling
