Successive POI Recommendation with Category Transition and Temporal Influence

I-Cheng Lin, Yi Shu Lu, Wen Yueh Shih, Jiun-Long Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

With the popularization of mobile devices and wireless networks, people are able to share their experience on points of interest (POIs) in social networks through 'check-ins.' Therefore, the problem of successive POI recommendation has been proposed to recommend some POIs to users so that the users are likely to check in at these POIs in the near future. In this paper, we propose a two-phase method to solve the problem of successive POI recommendation. First, we utilize the Matrix Factorization technique to analyze the interaction of users and their sequential check-in behavior with time influence and POI categories, and select the candidate categories that the user will visit. Then, after removing those POIs not belonging to the candidate categories, we fuse user preferences, temporal influence and geographical influence together and finally recommend the POIs with high scores to users. The experimental results on a real check-in dataset show that our recommendation method is better than several state-of-the-art methods in terms of precision and recall.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018
EditorsClaudio Demartini, Sorel Reisman, Ling Liu, Edmundo Tovar, Hiroki Takakura, Ji-Jiang Yang, Chung-Horng Lung, Sheikh Iqbal Ahamed, Kamrul Hasan, Thomas Conte, Motonori Nakamura, Zhiyong Zhang, Toyokazu Akiyama, William Claycomb, Stelvio Cimato
PublisherIEEE Computer Society
Pages57-62
Number of pages6
ISBN (Electronic)9781538626665
DOIs
StatePublished - 8 Jun 2018
Event42nd IEEE Computer Software and Applications Conference, COMPSAC 2018 - Tokyo, Japan
Duration: 23 Jul 201827 Jul 2018

Publication series

NameProceedings - International Computer Software and Applications Conference
Volume2
ISSN (Print)0730-3157

Conference

Conference42nd IEEE Computer Software and Applications Conference, COMPSAC 2018
CountryJapan
CityTokyo
Period23/07/1827/07/18

Keywords

  • Matrix factorization
  • Recommendation
  • Successive POI recommendation

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