论文标题
在交互日志中解决不确定的病例标识符：用户研究
Resolving Uncertain Case Identifiers in Interaction Logs: A User Study
论文作者
论文摘要
现代软件系统能够记录大量的用户操作，以供以后分析。此类用户交互数据的主要类型之一是单击数据：通过应用程序，网站或软件的图形元素，用户操作的数字轨迹。虽然随时可用，但单击数据通常会丢失一个案例概念：一个属性将事件从用户交互到软件中的特定过程实例。在本文中，我们提出了一种基于神经网络的技术来确定点击数据的案例概念，从而实现了对用户交互数据的过程挖掘和其他过程分析技术。我们描述了我们的方法，显示了其对大维数据集的可扩展性，并通过基于移动性共享公司相互作用数据产生的分段事件日志来验证其疗效。对公司中的领域专家的访谈表明，我们方法获得的案例概念可以导致可行的过程见解。
Modern software systems are able to record vast amounts of user actions, stored for later analysis. One of the main types of such user interaction data is click data: the digital trace of the actions of a user through the graphical elements of an application, website or software. While readily available, click data is often missing a case notion: an attribute linking events from user interactions to a specific process instance in the software. In this paper, we propose a neural network-based technique to determine a case notion for click data, thus enabling process mining and other process analysis techniques on user interaction data. We describe our method, show its scalability to datasets of large dimensions, and we validate its efficacy through a user study based on the segmented event log resulting from interaction data of a mobility sharing company. Interviews with domain experts in the company demonstrate that the case notion obtained by our method can lead to actionable process insights.
