一种基于知识元迁移的ESI研究前沿知识演进分析方法

Knowledge Evolution Analysis of ESI Research Fronts Based on Knowledge Element Migration

在前期研究的基础之上,本文提出了一种基于知识元迁移的ESI(essential science indicators)研究前沿知识演进分析方法,通过对研究前沿中的知识元迁移现象,进行定量分析和迁移程度计算,从语义分析和知识计算的角度,进一步探索研究前沿的演进机理。借助命名实体识别、词袋模型、PLDA(parallellatent Dirichlet allocation)主题模型、信息熵算法等文本语义挖掘和自然语言处理技术,通过设计贡献度指数CVI(contribution value index)和迁移度指数MVI(migration value index)两种计量指标,探究知识元的迁移规律。研究结果表明,以前沿主题中的个体知识元作为分析对象,可以从最为直接、最为细粒度的视角,对研究前沿随时间变化时内在知识结构特征的变迁规律进行挖掘,揭示领域知识要素在不同时期的演化状态,能够更为深入地回答研究前沿的追踪发展变迁问题,为面向学科前沿的科技情报工作提供方法论参考。

Based on previous research,this paper proposes a method for analyzing the knowledge evolution of ESI research fronts based on knowledge element migration.Through quantitative analysis of the knowledge element transfer phenomenon and calculation of migration degree,the mechanism of the evolution of ESI(essential science indicators)research is further explored from the perspective of semantic analysis and knowledge computing.With the help of named entity recognition,bag of words model,PLDA(parallel latent Dirichlet allocation)topic model,information entropy algorithm,and other text semantic mining and natural language processing technologies,this paper explores the migration rule of knowledge elements by designing contribution index CVI and migration index MVI.The results show that by taking individual knowledge element in the front topic as the analysis object,it is possible to mine the changing laws of the inherent knowledge structure characteristics of ESI research front over time from a direct and fine-grained perspective.The method can not only reveal the evolution status of domain knowledge elements in different periods but also identify and track changes in the development of the research front in a more in-depth manner.This study provides a methodological reference for the scientific and technological intelligence work focusing on identifying domain research fronts.