What question did this study set out to answer?

Develop an automated technique and interactive system to extract and visually summarize interpretable branching patterns and flow volumes from large-scale event sequence datasets.

June 1, 2017Computer Graphics Forum

CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences

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Authors

ZLZhicheng Liu BKBernard J Kerr MDMira Dontcheva

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Overview

Methodological study demonstrates rapid extraction and visualization of branching patterns across millions of event sequences, suggesting improved interpretability for complex flow analytics.

Key Points

Develop an automated technique and interactive system to extract and visually summarize interpretable branching patterns and flow volumes from large-scale event sequence datasets.
Engineered CoreFlow, a recursive tree-construction procedure that ranks events, divides sequences into groups, and trims sequences by the selected key event.
Built an interactive visual analytics system and evaluated performance through case studies across three distinct application domains.
Processed and generated branching patterns across datasets containing millions of events within a few seconds.
Achieved superior interpretability and visual flow summarization compared to existing sequential pattern mining approaches across real-world analytical problems.

Cite This Study

Liu et al. (2017) studied this question.

synapsesocial.com/papers/6a70d6cd2fdcb5703edb699d https://doi.org/10.1111/cgf.13208

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June 1, 2017Computer Graphics Forum

CoreFlow: Extracting and Visualizing Branching Patterns from Event Sequences

View Full Paper

Ask AI

Bookmark

Authors

ZLZhicheng Liu BKBernard J Kerr MDMira Dontcheva

Discussion

Member takes

Overview

Methodological study demonstrates rapid extraction and visualization of branching patterns across millions of event sequences, suggesting improved interpretability for complex flow analytics.

Key Points

Develop an automated technique and interactive system to extract and visually summarize interpretable branching patterns and flow volumes from large-scale event sequence datasets.
Engineered CoreFlow, a recursive tree-construction procedure that ranks events, divides sequences into groups, and trims sequences by the selected key event.
Built an interactive visual analytics system and evaluated performance through case studies across three distinct application domains.
Processed and generated branching patterns across datasets containing millions of events within a few seconds.
Achieved superior interpretability and visual flow summarization compared to existing sequential pattern mining approaches across real-world analytical problems.

Cite This Study

Liu et al. (2017) studied this question.

synapsesocial.com/papers/6a70d6cd2fdcb5703edb699d https://doi.org/10.1111/cgf.13208

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