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| Knowledge Evolution Analysis of ESI Research Fronts Based on Knowledge Element Migration |
| Sun Zhen1, Leng Fuhai2 |
1.Institute of Information Management, Shandong University of Technology, Zibo 255000
2.Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190 |
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Abstract 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.
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Received: 28 September 2020
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