Browsing2purchase: Online Customer Model for Sales Forecasting in an E-Commerce Site

Jinyoung Yeo, Sungchul Kim, Eunyee Koh, Seung Won Hwang, Nedim Lipka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

This paper covers a sales forecasting problem on e-commerce sites. To predict product sales, we need to understand customers' browsing behavior and identify whether it is for purchase purpose or not. For this goal, we propose a new customer model, B2P, of aggregating predictive features extracted from customers' browsing history. We perform experiments on a real world e-commerce site and show that sales predictions by our model are consistently more accurate than those by existing state-of-the-art baselines.

Original languageEnglish
Title of host publicationWWW 2016 Companion - Proceedings of the 25th International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages133-134
Number of pages2
ISBN (Electronic)9781450341448
DOIs
Publication statusPublished - 2016 Apr 11
Event25th International Conference on World Wide Web, WWW 2016 - Montreal, Canada
Duration: 2016 May 112016 May 15

Publication series

NameWWW 2016 Companion - Proceedings of the 25th International Conference on World Wide Web

Conference

Conference25th International Conference on World Wide Web, WWW 2016
Country/TerritoryCanada
CityMontreal
Period16/5/1116/5/15

Bibliographical note

Publisher Copyright:
© 2016 owner/author(s).

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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