随着每年出版的大量出版物, 学术数据迅速增长. 通过已发表的论文数据来准确、全面地呈现一个学者的科研水平和核心竞争力, 为大型科研机构的管理者、决策者或投资者提供辅助决策, 已成为文献大数据可视化的研究热点. 本文基于Web Of Science (WOS) 论文数据, (1) 采用结合算法和交互式可视化的方法提升数据质量, 针对WOS论文数据特征, 设计实体分组算法和分组可视化校正工具, 实现了人名和单位名的消歧; (2) 根据常用的学术竞争力指标, 设计了学者画像可视化方法; (3) 研发了一套基于论文数据的学者画像可视化系统, 并通过具体的真实案例证明了该系统的实用性和有效性.
With a large number of publications published every year, academic data grows rapidly. Through published paper data to accurately and comprehensively present a scholar’s scientific research level and core competitiveness so as to provide assistant decision-making for managers, decision-makers or investors of large-scale scientific research institutions, big data visualization has become a research hotspot of literature. This study based on Web Of Science (WOS) paper data, (1) in order to improve the quality of data, a combination of algorithms and interactive visualization is used to design entity grouping algorithm and grouping visualization correction tool for the data characteristics of WOS papers, which can eliminate the difference between person name and affiliation name; (2) according to the commonly used academic competitiveness index, the visualization method of scholar’s profile is designed; (3) a set of visualization system of scholar’s profile based on thesis data is developed, and the visualization system of scholar’s profile based on publicated papers is developed. The real case of body proves the practicability and effectiveness of the system.