Point-of-interest recommendation for location promotion in location-based social networks

Fei Yu, Zhijun Li, Shouxu Jiang, Shirong Lin

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

3 Scopus citations

Abstract

With the wide application of location-based social networks (LBSNs), point-of-interest (POI) recommendation has become one of the major services in LBSNs. The behaviors of users in LBSNs are mainly checking in POIs, and these checking-in behaviors are influenced by user's behavior habits and his/her friends. In social networks, social influence is often used to help businesses to attract more users. Each target user has a different influence on different POI in social networks. This paper selects the list of POIs with the greatest influence for recommending users. Our goals are to satisfy the target user's service need, and simultaneously to promote businesses' locations (POIs). This paper defines a POI recommendation problem for location promotion. Additionally, we use submodular properties to solve the optimization problem. At last, this paper conducted a comprehensive performance evaluation for our method using two real LBSN datasets. Experimental results show that our proposed method achieves significantly superior POI recommendations comparing with other state-of-the-art recommendation approaches in terms of location promotion.

Original languageEnglish (US)
Title of host publicationProceedings - 18th IEEE International Conference on Mobile Data Management, MDM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages344-347
Number of pages4
ISBN (Electronic)9781538639320
DOIs
StatePublished - Jun 29 2017
Event18th IEEE International Conference on Mobile Data Management, MDM 2017 - Daejeon, Korea, Republic of
Duration: May 29 2017Jun 1 2017

Publication series

NameProceedings - 18th IEEE International Conference on Mobile Data Management, MDM 2017

Other

Other18th IEEE International Conference on Mobile Data Management, MDM 2017
CountryKorea, Republic of
CityDaejeon
Period5/29/176/1/17

Keywords

  • Location promotion
  • Location-based social networks
  • POI recommendation
  • Social influence

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