论文标题
研究域信息挖掘和主题的科学论文演变的研究
Research on Domain Information Mining and Theme Evolution of Scientific Papers
论文作者
论文摘要
近年来，随着科学研究中社会投资的增加，各个领域的研究结果数量已大大增加。跨学科研究结果逐渐成为新兴的边界研究方向。大量研究结果之间存在一定的依赖性。在隔离单个研究领域时，很难有效地分析当今的科学研究结果。如何有效地使用大量科学论文来帮助研究人员成为挑战。本文从三个方面的科学和技术论文中介绍了国内外的研究状态：科学和技术论文的语义特征代表学，科学和技术论文的现场信息挖掘，以及科学和技术论文的现场信息挖掘以及科学和技术论文的研究主题进化规则的挖掘和预测。
In recent years, with the increase of social investment in scientific research, the number of research results in various fields has increased significantly. Cross-disciplinary research results have gradually become an emerging frontier research direction. There is a certain dependence between a large number of research results. It is difficult to effectively analyze today's scientific research results when looking at a single research field in isolation. How to effectively use the huge number of scientific papers to help researchers becomes a challenge. This paper introduces the research status at home and abroad in terms of domain information mining and topic evolution law of scientific and technological papers from three aspects: the semantic feature representation learning of scientific and technological papers, the field information mining of scientific and technological papers, and the mining and prediction of research topic evolution rules of scientific and technological papers.
