gSCorr: Modeling geo-social correlations for new check-ins on location-based social networks

Huiji Gao, Jiliang Tang, Huan Liu

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

130 Scopus citations

Abstract

Location-based social networks (LBSNs) have attracted an increasing number of users in recent years. The availability of geographical and social information of online LBSNs provides an unprecedented opportunity to study the human movement from their socio-spatial behavior, enabling a variety of location-based services. Previous work on LBSNs reported limited improvements from using the social network information for location prediction; as users can check-in at new places, traditional work on location prediction that relies on mining a user's historical trajectories is not designed for this "cold start" problem of predicting new check-ins. In this paper, we propose to utilize the social network information for solving the "cold start" location prediction problem, with a geo-social correlation model to capture social correlations on LBSNs considering social networks and geographical distance. The experimental results on a real-world LBSN demonstrate that our approach properly models the social correlations of a user's new check-ins by considering various correlation strengths and correlation measures.

Original languageEnglish (US)
Title of host publicationCIKM 2012 - Proceedings of the 21st ACM International Conference on Information and Knowledge Management
Pages1582-1586
Number of pages5
DOIs
StatePublished - Dec 19 2012
Event21st ACM International Conference on Information and Knowledge Management, CIKM 2012 - Maui, HI, United States
Duration: Oct 29 2012Nov 2 2012

Publication series

NameACM International Conference Proceeding Series

Other

Other21st ACM International Conference on Information and Knowledge Management, CIKM 2012
CountryUnited States
CityMaui, HI
Period10/29/1211/2/12

Keywords

  • geo-social correlation
  • location prediction
  • location recommendation
  • location-based social networks

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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    Gao, H., Tang, J., & Liu, H. (2012). gSCorr: Modeling geo-social correlations for new check-ins on location-based social networks. In CIKM 2012 - Proceedings of the 21st ACM International Conference on Information and Knowledge Management (pp. 1582-1586). (ACM International Conference Proceeding Series). https://doi.org/10.1145/2396761.2398477