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[目的 /意义]学科主题演化研究有助于掌握学科发展现状、研究热点、研究前沿和发展趋势等情况,是进行科技创新的基础,是面向科技创新的重要研究方向。[方法 /过程]提出一种语义分类的学科主题演化分析方法:将关键词分为研究问题、研究方法和研究技术3类,构建不同语义分类的共词网络;然后基于Fast Unfolding社区发现算法识别具有语义特征的社区(主题);利用相似度算法计算相邻子时期主题间的相似度,构建学科主题演化图谱,以分析某学科领域研究问题、研究方法和研究技术的变化,实现深度、细致的学科主题演化分析。[结果 /结论]通过对2012-2015年CNKI数据库收录的我国大数据研究领域相关论文数据的处理分析,证明该方法的准确性和有效性。
[Purpose / Significance] Thematic evolution studies of disciplines help to grasp the status quo of subject development, research hot spots, research frontiers and development trends, which are the basis for scientific and technological innovation and an important research direction for scientific and technological innovation. [Methods / Processes] This paper proposes a semantic categorization subject evolution analysis method: the key words are divided into three categories: research questions, research methods and research techniques to construct a common word network with different semantic categories; and then based on the Fast Unfolding community discovery algorithm Semantic characteristics of the community (theme); the use of similarity algorithm to calculate the similarity between adjacent sub-topics, the construction of thematic evolution map to analyze a subject area of research problems, research methods and research techniques to achieve the depth and meticulous Subject Subject Evolutionary Analysis. [Results / Conclusions] Through the analysis of the data of the related papers in the field of big data research collected in CNKI database in 2012-2015, the accuracy and effectiveness of the method are proved.