企业战略性知识轮廓:化工专利数据挖掘与分析  

Firms' Strategic Knowledge Profiles: Chemical Technology Patent Data Mining and Analysis

作　　者：王江[1] 郭鑫彬 Wang Jiang;Guo Xinbin(School of Economics and Management,Beijing University of Chemical Technology,Beijing 100029)

机构地区：[1]北京化工大学经济管理学院,北京100029

出　　处：《情报杂志》2021年第8期53-61,共9页Journal of Intelligence

基　　金：国家社会科学基金项目“京津冀地区大气污染治理利基项目间学习研究”(编号:17BGL267)研究成果之一。

摘　　要：[目的/意义]在知识经济时代,专利分析能更好地接近企业潜在战略模式和技术核心的发展轨迹。[方法/过程]以化工领域优秀企业的专利数据库为例,将LDA主题模型、聚类分析和分层时间序列趋势预测相结合,对企业战略性知识轮廓进行分析和预测。[结果/结论]研究结果显示,化工行业内各企业在战略性知识轮廓上的不同,揭示了化工行业中新兴和衰退的知识领域的动态,清晰展现出行业领导者受绿色化工理念所影响的技术战略的演变。[Purpose/Significance]In the era of knowledge economy,patent analysis can better approach the trajectory of firm's potential strategic pattern and technological core.[Method/Process]We take the patent databases of excellent firms in chemical industry as the example and combine LDA(Latent Dirichlet Allocation)topic model,clustering analysis and hierarchical time series'trend prediction to analyze and predict the firm's strategic knowledge profiles.[Result/Conclusion]The research results show the differences in the strategic knowledge profiles between various firms in chemical industry and it reveals the dynamics of the emerging and declining knowledge fields in chemical industry that clearly shows the evolution of the technology strategy made by industry leaders who are influenced by the concept of green chemical industry.

关 键 词：专利分析 主题模型 聚类分析 趋势预测 绿色化工 

分 类 号：G302[文化科学]