论文标题
事件序列数据的视觉分析调查
Survey on Visual Analysis of Event Sequence Data
论文作者
论文摘要
事件序列数据记录记录在发生时间顺序的离散事件。通常在各种应用中观察到它们，从电子健康记录到网络日志，具有大规模，高维和异质性的特征。事件序列数据的这种高复杂性使分析师很难手动探索和查找模式，从而从视觉分析技术中增加了对计算和感知辅助工具的需求，从而从事件序列数据集中提取和传达洞察力。在本文中，我们回顾了最先进的视觉分析方法，以我们建议的设计空间来表征它们，并根据分析任务和应用程序对其进行分类。根据我们对相关文献的回顾，我们还确定了剩余的一些研究挑战和未来的研究机会。
Event sequence data record series of discrete events in the time order of occurrence. They are commonly observed in a variety of applications ranging from electronic health records to network logs, with the characteristics of large-scale, high-dimensional, and heterogeneous. This high complexity of event sequence data makes it difficult for analysts to manually explore and find patterns, resulting in ever-increasing needs for computational and perceptual aids from visual analytics techniques to extract and communicate insights from event sequence datasets. In this paper, we review the state-of-the-art visual analytics approaches, characterize them with our proposed design space, and categorize them based on analytical tasks and applications. From our review of relevant literature, we have also identified several remaining research challenges and future research opportunities.
