A Set-based Visual Analytics Approach to Analyze Retail Data
| dc.contributor.author | Adnan, Muhammad | en_US |
| dc.contributor.author | Ruddle, Roy A. | en_US |
| dc.contributor.editor | Christian Tominski and Tatiana von Landesberger | en_US |
| dc.date.accessioned | 2018-06-02T17:57:03Z | |
| dc.date.available | 2018-06-02T17:57:03Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | This 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.sectionheaders | Applications | |
| dc.description.seriesinformation | EuroVis Workshop on Visual Analytics (EuroVA) | |
| dc.identifier.doi | 10.2312/eurova.20181110 | |
| dc.identifier.isbn | 978-3-03868-064-2 | |
| dc.identifier.pages | 37-41 | |
| dc.identifier.uri | https://doi.org/10.2312/eurova.20181110 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/eurova20181110 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Human | |
| dc.subject | centered computing | |
| dc.subject | Visual analytics | |
| dc.subject | Information systems | |
| dc.subject | Data mining | |
| dc.title | A Set-based Visual Analytics Approach to Analyze Retail Data | en_US |