ICE: Identify and Compare Event Sequence Sets through Multi-Scale Matrix and Unit Visualizations

TL;DR

ICE is an interactive visualization tool that helps analysts explore, identify, and compare event sequence sets at multiple granularities using multi-scale matrix and unit visualizations, demonstrated on real-world datasets.

Contribution

The paper introduces ICE, a novel interactive visualization system that enables multi-scale exploration and comparison of event sequence data through innovative matrix and unit visualization techniques.

Findings

Effective identification of event sequence sets at multiple levels

Supports comparison of sequences based on prefixes and suffixes

Demonstrated usefulness on real-world datasets

Abstract

Comparative analysis of event sequence data is essential in many application domains, such as website design and medical care. However, analysts often face two challenges: they may not always know which sets of event sequences in the data are useful to compare, and the comparison needs to be achieved at different granularity, due to the volume and complexity of the data. This paper presents, ICE, an interactive visualization that allows analysts to explore an event sequence dataset, and identify promising sets of event sequences to compare at both the pattern and sequence levels. More specifically, ICE incorporates a multi-level matrix-based visualization for browsing the entire dataset based on the prefixes and suffixes of sequences. To support comparison at multiple levels, ICE employs the unit visualization technique, and we further explore the design space of unit visualizations for event sequence comparison tasks. Finally, we demonstrate the effectiveness of ICE with three real-world datasets from different domains.