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Multimedia Tools and Applications

, Volume 77, Issue 17, pp 21935–21945 | Cite as

Profiling users by online shopping behaviors

  • Huan Yan
  • Zifeng Wang
  • Tzu-Heng Lin
  • Yong Li
  • Depeng Jin
Article
  • 585 Downloads

Abstract

Online shopping has been prevalent in our daily life. Profiling users and understanding their browsing behaviors are critical for enhancing shopping experience and maximizing sales revenue. In this paper, based on a one-month dataset recording 2 million users’ 67 million online shopping and browsing logs, we seek to understand how users browse and shop products, and how distinct these behaviors are. We find that there exist dedicate groups of users that prefer certain product categories corresponding to similar demands. Moreover, distinct differences of behaviors exist in categories, where repetitive and targeted browsing are two major prevalent patterns.

Keywords

Social network User behavior analytics Data analysis 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  • Huan Yan
    • 1
  • Zifeng Wang
    • 1
  • Tzu-Heng Lin
    • 1
  • Yong Li
    • 1
  • Depeng Jin
    • 1
  1. 1.Tsinghua National Laboratory for Information Science and Technology, Department of Electronic EngineeringTsinghua UniversityBeijingChina

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