INTERACTIVE EXPLORATION of TEMPORAL EVENT SEQUENCES Krist Wongsuphasawat Doctor of Philosophy, 2012
ABSTRACT Title of dissertation: INTERACTIVE EXPLORATION OF TEMPORAL EVENT SEQUENCES Krist Wongsuphasawat Doctor of Philosophy, 2012 Dissertation directed by: Professor Ben Shneiderman Department of Computer Science Life can often be described as a series of events. These events contain rich in- formation that, when put together, can reveal history, expose facts, or lead to discov- eries. Therefore, many leading organizations are increasingly collecting databases of event sequences: Electronic Medical Records (EMRs), transportation incident logs, student progress reports, web logs, sports logs, etc. Heavy investments were made in data collection and storage, but difficulties still arise when it comes to making use of the collected data. Analyzing millions of event sequences is a non-trivial task that is gaining more attention and requires better support due to its complex nature. Therefore, I aimed to use information visualization techniques to support exploratory data analysis|an approach to analyzing data to formulate hypothe- ses worth testing|for event sequences. By working with the domain experts who were analyzing event sequences, I identified two important scenarios that guided my dissertation: First, I explored how to provide an overview of multiple event sequences? Lengthy reports often have an executive summary to provide an overview of the report. Unfortunately, there was no executive summary to provide an overview for event sequences. Therefore, I designed LifeFlow, a compact overview visualization that summarizes multiple event sequences, and interaction techniques that supports users' exploration. Second, I examined how to support users in querying for event sequences when they are uncertain about what they are looking for. To support this task, I developed similarity measures (the M&M measure 1-2 ) and user interfaces (Similan 1-2 ) for querying event sequences based on similarity, allowing users to search for event sequences that are similar to the query.
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