国内文本挖掘的热点主题和前沿演进——基于CNKI收录文献的可视化分析

Hot Topics and Frontier Evolution of Text Mining in China—A Visual Analysis of the Documents Collected by CNKI

摘要: 使用数据可视化软件CiteSpace基于中国学术网络出版总库(CNKI)收录的关于研究文本挖掘的中文文献对机构、作者、关键词等绘制图谱并进行分析与评述。经研究表现出三方面结论：1) 各研究机构之间合作比较分散，合作较少；2) 各学者间的交流与合作不显著，合作意识仍然有待提高；3) 研究的热点主题有web挖掘、文本分类、中成药、西药、数据分层算法、大数据文本、情感分析；大数据下文本挖掘与情感分析为我国文本挖掘研究的主要研究趋势。

Abstract: Data visualization software CiteSpace was used to analyze and study the institutions, authors and keywords of Chinese literature on text mining collected by CNKI. The research shows three con-clusions: 1) There is little cooperation between research institutions. 2) There is little communi-cation and cooperation among scholars, and the sense of cooperation still needs to be improved. 3) The hot topics include web mining, text classification, Chinese patent medicine, western medicine, data stratification algorithm, big data text and emotion analysis. Text mining and emotion analysis under big data are the main research trend of text mining in China.