COPE: Interactive Exploration of Co-Occurrence Patterns in Spatial Time Series

dc.contributor.VIAF65983012 (Zhang, K)
dc.contributor.authorLi, J.
dc.contributor.authorChen, S.
dc.contributor.authorZhang, Kang
dc.contributor.authorAndrienko, G.
dc.contributor.authorAndrienko, N.
dc.contributor.utdAuthorZhang, Kang
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dc.description.abstractSpatial time series is a common type of data dealt with in many domains, such as economic statistics and environmental science. There have been many studies focusing on finding and analyzing various kinds of events in time series; the term ‘event’ refers to significant changes or occurrences of particular patterns formed by consecutive attribute values. We focus on a further step in event analysis: finding and exploring events that frequently co-occurred with a target class of similar events having occurred repeatedly over a period of time. This type of analysis can provide important clues for understanding the formation and spreading mechanisms of events and interdependencies among spatial locations. We propose a visual exploration framework COPE (Co-Occurrence Pattern Exploration), which allows users to extract events of interest from data and detect various co-occurrence patterns among them. Case studies and expert reviews were conducted to verify the effectiveness and scalability of COPE using two real-world datasets.
dc.description.departmentErik Jonsson School of Engineering and Computer Science
dc.description.sponsorshipNational NSFC project (Grant numbers 61602340, 61572348); National High-tech R&D Program (863 Grant number 215AA020506), German Priority Research Program SPP 1894 on Volunteered Geographic Information, EU project Track & Know (Grant agreement 780754).
dc.identifier.bibliographicCitationLi, J., S. Chen, K. Zhang, G. Andrienko, et al. 2018. "COPE: Interactive exploration of co-occurrence patterns in spatial time series." IEEE Transactions on Visualization and Computer Graphics, doi:10.1109/TVCG.2018.2851227
dc.publisherIEEE Computer Society
dc.rights©2018 IEEE
dc.source.journalIEEE Transactions on Visualization and Computer Graphics
dc.subjectData mining
dc.subjectInformation visualization
dc.subjectTime-series analysis
dc.subjectVisual analytics
dc.titleCOPE: Interactive Exploration of Co-Occurrence Patterns in Spatial Time Series


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