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dc.contributor.authorRees, Dylanen_US
dc.contributor.authorRoberts, Richard C.en_US
dc.contributor.authorLaramee, Robert S.en_US
dc.contributor.authorBrookes, Paulen_US
dc.contributor.authorD'Cruze, Tonyen_US
dc.contributor.authorSmith, Gary A.en_US
dc.contributor.editor{Tam, Gary K. L. and Vidal, Francken_US
dc.date.accessioned2018-09-19T15:15:13Z
dc.date.available2018-09-19T15:15:13Z
dc.date.issued2018
dc.identifier.isbn978-3-03868-071-0
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/cgvc20181209
dc.identifier.urihttps://doi.org/10.2312/cgvc.20181209
dc.description.abstractWith four percent of the working population employed in call centers in both the United States and the UK, the contact center industry represents a sizable proportion of modern industrial landscapes. As with most modern industries, data collection is de rigueur, producing gigabytes of call records that require analysis. The scatterplot is a well established and understood form of data visualization dating back to the 17th century. In this paper we present an application for visualizing large call centre data sets using hardware-accelerated scatterplots. The application utilizes a commodity graphics card to enable visualization of a month's worth of data, enabling fast filtering of multiple attributes. Filtering is implemented using the Open Computing Language (OpenCL), providing significant performance improvement over traditional methods. We demonstrate the value of our application for exploration and analysis of millions of call events from a real-world industry partner. Domain expert feedback from our industrial partners is reported.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectInformation visualization
dc.subjectVisualization toolkits
dc.titleGPU-Assisted Scatterplots for Millions of Call Eventsen_US
dc.description.seriesinformationComputer Graphics and Visual Computing (CGVC)
dc.description.sectionheadersVisualization I
dc.identifier.doi10.2312/cgvc.20181209
dc.identifier.pages71-79


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