Search Wandering Score: Predicting Timings of Online Shopping based on Wandering in User's Web Search Queries

Kota Tsubouchi, Wataru Sasaki, Tadashi Okoshi, Jin Nakazawa

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

Abstract

Many researchers and companies have engaged in estimating users' interests so that an online shopping system can tell what he/she wants now. This paper tackles the next challenge in online shopping, i.e., predicting the times that users go shopping online. To predict the timing of online shopping, we focus on wandering behavior in web search activities and propose a search wandering score (SWS). Online shopping behavior can be categorized into three states: wandering shop-ping, focused shopping, and others. Wandering shopping is a state in which users make purchases in high SWS situations; focused shopping is a state in which users buy things in low SWS situations. Unlike previous studies, our work is based on an analysis of large-scale data containing shopping and search logs produced by approximately 200,000 users of a real web portal site for over a year. The results of an extensive evaluation show that our methodology can predict user's future shopping behavior types with 86% accuracy. This research is the first step towards understanding the relationship between users' mental states and their online shopping behavior.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Big Data, Big Data 2020
EditorsXintao Wu, Chris Jermaine, Li Xiong, Xiaohua Tony Hu, Olivera Kotevska, Siyuan Lu, Weijia Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1681-1688
Number of pages8
ISBN (Electronic)9781728162515
DOIs
Publication statusPublished - 2020 Dec 10
Event8th IEEE International Conference on Big Data, Big Data 2020 - Virtual, Atlanta, United States
Duration: 2020 Dec 102020 Dec 13

Publication series

NameProceedings - 2020 IEEE International Conference on Big Data, Big Data 2020

Conference

Conference8th IEEE International Conference on Big Data, Big Data 2020
CountryUnited States
CityVirtual, Atlanta
Period20/12/1020/12/13

Keywords

  • Online Shopping Timing
  • Search Wandering
  • User Classification

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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