Visitor Behavior Analysis Based on Large-Scale Wi-Fi Location Data

Masaki Maruta, Yuta Sano, Kohei Yamaguchi, Tsunenori Mine

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

1 Citation (Scopus)

Abstract

The paper aims to interpret visitor behaviors by analyzing a large scale Wi-Fi location data obtained at Interop Tokyo 2014. We first detected a situation of a visitor's stay at a booth, calculated the sojourn time of the visitor and represented each visitor as a booth vector whose element value is the total sojourn time of the visitor at a booth. Then, we classified the visitors by k-Means. By using category labels of each booth, we analyzed characteristics of clusters. The results illustrate that some categories appear at the top rank of most clusters, and the area of the booths included in each cluster is mostly some specific small one, not the entire one.

Original languageEnglish
Title of host publicationProceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015
EditorsSachio Hirokawa, Kiyota Hashimoto, Tokuro Matsuo, Tsunenori Mine
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages55-60
Number of pages6
ISBN (Electronic)9781479999583
DOIs
Publication statusPublished - Jan 6 2016
Event4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015 - Okayama, Japan
Duration: Jul 12 2015Jul 16 2015

Publication series

NameProceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015

Other

Other4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015
CountryJapan
CityOkayama
Period7/12/157/16/15

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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