1 research outputs found
ICE: Identify and Compare Event Sequence Sets through Multi-Scale Matrix and Unit Visualizations
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