ESI遴选研究前沿与高校学科方向多角度匹配分析——以D高校环境/生态学科为例
Analysis of the Multi-Angle Matching between ESI Selected Research Frontiers and University Academic Directions:A Case Study of Environmental/Ecological Disciplines at D University
高健 1秦奋 1宋妙茹1
作者信息
- 1. 大连理工大学图书馆 大连 116024
- 折叠
摘要
[目的/意义]以大连理工大学环境/生态学科为案例,目的在于构建一个系统性分析框架,精准识别ESI遴选的研究前沿,并评估其与高校学科方向的契合度.研究的核心意义在于促进学科创新和教育质量的提高,同时为高校提供战略规划的决策支持.本文将解决的关键问题包括:如何识别并对接学科发展与国际科研前沿,以及如何通过深入分析D大学环境/生态学科的学术成果,挖掘学科发展潜力,应对挑战,为学科建设和科研管理提供数据驱动的策略建议.[方法/过程]选取ESI环境/生态学科研究前沿领域和D大学过去10年相应学科论文为研究对象,运用Python语言,通过文本挖掘、机器学习及图谱分析等前沿技术手段,开展多维度的学科方向匹配和差异性分析.[结果/结论]关键词匹配、LDA模型和知识图谱多方法并行的匹配分析,能够全面准确地服务于ESI前沿领域与高校战略发展的规划,为科研管理提供参考.
Abstract
[Purpose/Significance]Against the backdrop of global technological competition and education-al reform,higher education institutions need to keep pace with the forefront of international scientific research to achieve synchronized upgrading of their disciplinary development strategies.Taking the Environment/Ecology dis-cipline of Dalian University of Technology as a case study,the purpose of this research is to construct a systematic analytical framework aimed at accurately identifying ESI-selected research frontiers and assessing their alignment with the disciplinary directions of universities.The core significance of the study lies in promoting disciplinary in-novation and the improvement of educational quality,while also providing decision support for strategic planning in higher education institutions.The key issues addressed in this paper include:how to identify and connect disci-plinary development with the international scientific research frontier,and how to analyze the academic achieve-ments of the Environment/Ecology discipline at University D in depth,to explore the potential for disciplinary development,address challenges,and provide data-driven strategic recommendations for disciplinary construction and scientific research management.The aim is to assist universities in promptly grasping the trends of international scientific research,exploring emerging areas within disciplines,and optimizing their own disciplinary construction.[Method/Process]The study focuses on the ESI research fronts in environment/ecology and the corresponding discipline papers from University D over the past 10 years.Utilizing e Python,the study employs cutting-edge techniques such as text mining,machine learning,and graph analysis to conduct multidimensional analysis of dis-ciplinary alignment and differentiation.[Result/Conclusion]The parallel use of keyword matching,LDA(Latent Dirichlet Allocation)model,and knowledge graph analysis can serve the planning of ESI fronts and the strategic development of universities comprehensively and accurately,providing a reference for scientific research manage-ment.
关键词
ESI研究前沿/Python语言/机器学习/知识图谱Key words
ESI research fronts/python/machine learning/knowledge graph引用本文复制引用
出版年
2024
NETL
NSTL
万方数据