摘要
互联网的快速发展带动了人们的购物行为,越来越多的人群习惯于进行网购,随之产生的是各种各样的网购交易数据,这些数据复杂、多维,并且具有时序性,消费者的购买行为是众多电商及分析人员的研究热点.本文提出了一种以个体为中心,基于商品引力对商品层级结构数据与消费者的购物行为特征的可视分析方法,使分析者更方便地观察每位消费者的消费行为,从而得到他们的购物特点.最后,给出实验结果,证明方法的有效性.
The rapid development of the Internet has led to increasing online shopping and accumulated large amount of complicated, multi-dimensional and temporal transaction data. Many e-retailers and analysts are focusing on these data to study customers＇ shopping behaviors. In this study, based on product gravity, a visual analytical method focusing on individuals is proposed to analyze hierarchic production data and the features of shopping behaviors, which allows analysts to observe each consumer＇s shopping behaviors more directly so as to discover the features of their shopping behaviors more easily. Finally, the experimental results are presented to prove the effectiveness of the method.
出处
《计算机系统应用》
2018年第2期1-8,共8页
Computer Systems & Applications
基金
国家"863"高技术研究发展计划项目(2015AA01A302)
国家自然科学基金(91530324)
关键词
时序数据
层级结构
商品引力
购物行为
可视化
time-series data
hierarchy
product gravity
shopping behavior
visualization
