A Point-of-Interest Recommendation Method Using Location Similarity

Jun Zeng, Yinghua Li, Feng Li, Junhao Wen, Sachio Hirokawa

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

4 Citations (Scopus)

Abstract

POI recommendation aims to recommend places which users have not visited before. In this paper, we proposed a POI recommendation method using location similarity, which assumes that people may be interested in the places that are similar with the places that they have been to before. In order to calculate the similarity of locations, we proposed a novel method using time slots. Every two hours can be considered as a time slot. In other words, one day can be segmented into 12 time slots. For each location, the check-in times in each time slot can be collected. These check-in times can form a vector, which can be used to calculate the similarity of two locations. According to the similarity, the score of each unvisited locations can be calculated and sorted. Finally, the POI recommendation can be generated from the top-n unvisited locations. The experiment results show that the proposed method is effective.

Original languageEnglish
Title of host publicationProceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
EditorsKiyota Hashimoto, Naoki Fukuta, Tokuro Matsuo, Sachio Hirokawa, Masao Mori, Masao Mori
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages436-440
Number of pages5
ISBN (Electronic)9781538606216
DOIs
Publication statusPublished - Nov 15 2017
Event6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 - Hamamatsu, Shizuoka, Japan
Duration: Jul 9 2017 → …

Publication series

NameProceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017

Other

Other6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
CountryJapan
CityHamamatsu, Shizuoka
Period7/9/17 → …

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

Fingerprint Dive into the research topics of 'A Point-of-Interest Recommendation Method Using Location Similarity'. Together they form a unique fingerprint.

  • Cite this

    Zeng, J., Li, Y., Li, F., Wen, J., & Hirokawa, S. (2017). A Point-of-Interest Recommendation Method Using Location Similarity. In K. Hashimoto, N. Fukuta, T. Matsuo, S. Hirokawa, M. Mori, & M. Mori (Eds.), Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 (pp. 436-440). [8113284] (Proceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IIAI-AAI.2017.122