Han Yi, Abowd Gregory D, Stasko John
IEEE Trans Vis Comput Graph. 2025 Mar;31(3):1772-1784. doi: 10.1109/TVCG.2024.3370637. Epub 2025 Jan 30.
Application developers frequently augment their code to produce event logs of specific operations performed by their users. Subsequent analysis of these event logs can help provide insight about the users' behavior relative to its intended use. The analysis process typically includes both event organization and pattern discovery activities. However, most existing visual analytics systems for interaction log analysis excel at supporting pattern discovery and overlook the importance of flexible event organization. This omission limits the practical application of these systems. Therefore, we developed a novel visual analytics system called IntiVisor that implements the entire end-to-end interaction analysis approach. An evaluation of the system with interaction data from four visualization applications showed the value and importance of supporting event organization in interaction log analysis.
应用程序开发者经常扩充其代码，以生成用户执行的特定操作的事件日志。随后对这些事件日志进行分析，有助于深入了解用户相对于预期用途的行为。分析过程通常包括事件组织和模式发现活动。然而，大多数现有的用于交互日志分析的可视化分析系统擅长支持模式发现，却忽视了灵活的事件组织的重要性。这种疏忽限制了这些系统的实际应用。因此，我们开发了一种名为IntiVisor的新型可视化分析系统，该系统实现了完整的端到端交互分析方法。使用来自四个可视化应用程序的交互数据对该系统进行评估，结果表明了在交互日志分析中支持事件组织的价值和重要性。
