Exploring multivariate event sequences using rules, aggregations, and selections

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Abstract

Multivariate event sequences are ubiquitous: travel history, telecommunication conversations, and server logs are some examples. Besides standard properties such as type and timestamp, events often have other associated multivariate data. Current exploration and analysis methods either focus on the temporal analysis of a single attribute or the structural analysis of the multivariate data only. We present an approach where users can explore event sequences at multivariate and sequential level simultaneously by interactively defining a set of rewrite rules using multivariate regular expressions. Users can store resulting patterns as new types of events or attributes to interactively enrich or simplify event sequences for further investigation. In Eventpad we provide a bottom-up glyph-oriented approach for multivariate event sequence analysis by searching, clustering, and aligning them according to newly defined domain specific properties. We illustrate the effectiveness of our approach with real-world data sets including telecommunication traffic and hospital treatments.
Original languageEnglish
Article number8019837
Pages (from-to)532-541
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Volume24
Issue number1
Early online date29 Aug 2017
DOIs
Publication statusPublished - 1 Jan 2018

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