CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences
CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences
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DOI：
10.1111/cgf.13208
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发表时间：
2017-06-01
影响因子：
2.5
通讯作者：
Wilson, Alan
中科院分区：
文献类型：
--
作者：
Liu, Zhicheng;Kerr, Bernard;Wilson, Alan
具有高事件基数和长序列的事件序列数据集难以可视化和分析。特别是，很难生成路径和流量的高级视觉摘要。挖掘和可视化频繁顺序模式的现有方法看起来很有前途，但在可伸缩性、可解释性和实用性方面存在局限性。我们提出了CoreFlow，一种在事件序列中自动提取和可视化分支模式的技术。CoreFlow通过递归地应用一个三步过程来构建一个树：对事件进行排序，将序列分成组，并根据所选事件修剪序列。结果树包含作为节点的关键事件，链接表示关键事件之间的聚合流。基于CoreFlow，我们开发了一个交互式的事件序列分析系统。我们的方法可以在几秒钟内计算数百万个事件的分支模式，与以前的工作相比，提取模式的可解释性得到了改进。我们还介绍了在三个不同领域中使用该系统的案例研究，并讨论了将CoreFlow应用于实际分析问题的成功和失败案例。这些案例研究唤起了对度量和模型的未来研究，以评估事件序列的视觉摘要的质量。
Event sequence datasets with high event cardinality and long sequences are difficult to visualize and analyze. In particular, it is hard to generate a high level visual summary of paths and volume of flow. Existing approaches of mining and visualizing frequent sequential patterns look promising, but have limitations in terms of scalability, interpretability and utility. We propose CoreFlow, a technique that automatically extracts and visualizes branching patterns in event sequences. CoreFlow constructs a tree by recursively applying a three-step procedure: rank events, divide sequences into groups, and trim sequences by the chosen event. The resulting tree contains key events as nodes, and links represent aggregated flows between key events. Based on CoreFlow, we have developed an interactive system for event sequence analysis. Our approach can compute branching patterns for millions of events in a few seconds, with improved interpretability of extracted patterns compared to previous work. We also present case studies of using the system in three different domains and discuss success and failure cases of applying CoreFlow to real-world analytic problems. These case studies call forth future research on metrics and models to evaluate the quality of visual summaries of event sequences.