关键词: 聚类算法, 可视分析, 交互设计, 企业日志数据

Abstract: Enterprise log data, includes employee web access logs, mail logs, which is the record kept by the system when employees use the network service inside the enterprise. To a certain extent, these logs reflect the internal organizational structure, the daily working patterns of employees, and various abnormal situations. The analysis of the log data helps the company’s senior management to control the operation of the enterprise in a timely manner, and discover potential threats of the enterprise, thereby helping to make better decisions. Most of the existing enterprise log analysis methods use algorithms such as data mining and machine learning to analyze on a single data basis. This paper argues that： combining data-centric analysis algorithms with human-centered interactive visualizations can simultaneously exploit the advantages of algorithms and humans, visual analysis method can more effectively combine multi-source heterogeneous, time-varying, multi-dimensional log data analysis to provide multi-angle analysis. To this end, this paper proposes a visualization method which designs and implements a visual analysis system for employee work behavior for enterprise log data EWB-VIS. Experiments are conducted on the public dataset provided by the ChinaVis2018 Challenge to demonstrate the availability of the system and the effectiveness of the relevant visualization methods.

Key words: clustering algorithm, visual analysis, interaction design, enterprise log data