面向多源数据的高校创新知识发现研究——以“人工智能”领域为例

Research on Innovative Knowledge Discovery in Universities Based on Multi Source Data

通过识别高校人工智能领域的研究内容,可以梳理研究主题的演化路径。针对高校人工智能主题识别语义杂乱等问题,文中以知网2014—2023年人工智能教育的核心期刊文献为数据源,利用LDA模型抽取研究主题,从一致性、主题强度等计量指标入手,发现高校人工智能领域热点研究主题的演化变迁。分析结果表明,文中提出的方法可从宏微观全面梳理人工智能研究主题的演化路径,有利于探究高校人工智能研究的前沿。

By identifying the research content in the field of artificial intelligence in universities,the evolution path of research topics can be sorted out.In response to the problem of semantic confusion in artificial intelligence topic recognition in universities,this paper uses core journal literature on artificial intelligence education from CNKI from 2014 to 2023 as the data source,extracts research topics using LDA models,and starts with measurement indicators such as consistency and topic intensity to discover the evolution and changes of hot research topics in the field of artificial intelligence in universities.The empirical analysis results indicate that the proposed method can comprehensively sort out the evolutionary path of artificial intelligence research topics from macro and micro perspectives,which is conducive to exploring the forefront of artificial intelligence research in universities.