A Set-based Visual Analytics Approach to Analyze Retail Data

dc.contributor.authorAdnan, Muhammaden_US
dc.contributor.authorRuddle, Roy A.en_US
dc.contributor.editorChristian Tominski and Tatiana von Landesbergeren_US
dc.date.accessioned2018-06-02T17:57:03Z
dc.date.available2018-06-02T17:57:03Z
dc.date.issued2018
dc.description.abstractThis paper explores how a set-based visual analytics approach could be useful for analyzing customers' shopping behavior, and makes three main contributions. First, it describes the scale and characteristics of a real-world retail dataset from a major supermarket. Second, it presents a scalable visual analytics workflow to quickly identify patterns in shopping behavior. To assess the workflow, we conducted a case study that used data from four convenience stores and provides several insights about customers' shopping behavior. Third, from our experience with analyzing real-world retail data and comments made by our industry partner, we outline four research challenges for visual analytics to tackle large set intersection problems.en_US
dc.description.sectionheadersApplications
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.identifier.doi10.2312/eurova.20181110
dc.identifier.isbn978-3-03868-064-2
dc.identifier.pages37-41
dc.identifier.urihttps://doi.org/10.2312/eurova.20181110
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurova20181110
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectVisual analytics
dc.subjectInformation systems
dc.subjectData mining
dc.titleA Set-based Visual Analytics Approach to Analyze Retail Dataen_US
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