关键词: 科学知识图谱, 共现网络, 共现分析, 可视化, 科学知识图谱绘制工具

Abstract:

[Purpose/Significance] Mapping knowledge domain of co-occurrence science plays an increasingly important role in the study of detecting research hotspots and trends, discovering academic community,measuring and visualizing interdisciplinary integration and so on. So it is necessary to profoundly explore its key techniques and tools. [Design/Methodology] This paper divides the process of mapping knowledge domain construction in co-occurrence science into three levels: knowledge unit extraction, knowledge network construction, and knowledge discovery and visualization, and analyzes the key technologies according to some main co-occurrence mapping softwares. Then a co-occurrence network construction model with wide adaptability is proposed based on the actors, events and transforming methods. [Findings/Conclusion] The developing trends and major challenges have been pointed out, including the fine granularity, objectivity and innovation of knowledge unit selection; the differentiation, semantics and diversity of cooccurrence network construction; the improvement of statistical analyzing methods and the comparative study on revealing ability of different map scientific structures. [Originality/Value]  Theories and tools of co-occurrence map construction have been thoroughly analyzed in details, and the co-occurrence network construction model and the developing trends have been put forward.

Key words: Map of scientific knowledge, Co-occurrence network, Co-occurrence analysis, Visualization, Tools of mapping scientific knowledge