A Set-based Visual Analytics Approach to Analyze Retail Data
A Set-based Visual Analytics Approach to Analyze Retail Data
复制标题
DOI：
10.2312/eurova.20181110
复制
发表时间：
2018-06
期刊：
影响因子：
--
通讯作者：
M. Adnan;R. Ruddle
中科院分区：
文献类型：
--
作者：
M. Adnan;R. Ruddle
本文探讨了基于集合的视觉分析方法如何用于分析客户的购物行为，并做出了三个主要贡献。首先，它描述了来自大型超市的真实零售数据集的规模和特征。其次，它提供了一个可扩展的可视化分析工作流来快速识别购物行为的模式。为了评估工作流程，我们进行了一个案例研究，使用了来自四家便利店的数据，并提供了一些关于顾客购物行为的见解。第三，根据我们分析真实零售数据的经验和我们的行业合作伙伴的评论，我们概述了视觉分析解决大集合交集问题的四个研究挑战。
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.