Social personalized ranking embedding for next POI recommendation

Yan Long, Pengpeng Zhao, Victor S. Sheng, Guanfeng Liu, Jiajie Xu, Jian Wu, Zhiming Cui

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

9 Scopus citations


As the increasing popularity of the applications of location-based services, points-of-interest (POI) recommendation has become a great value part to help users explore their surrounding living environment and improve the quality of life. Recently, some researchers proposed next POI recommendation, which not only exploiting the users personal interests but also considers the sequential information of users check-ins. There are some next POI recommendation models exploit Metric Embedding method to improve recommendation performance and efficiency. However, these approaches not consider social relations in next POI recommendation, which is challenging due to social relations are noisy and sparse. To this end, in this paper, we proposed a Social Personalized Ranking Embedding (SPRE) model, which integrates user personalization and social relations into consideration, to learn the social relations by social embedding for next POI recommendation. Our experiments on a real-world large-scale dataset (Foursquare) results show that our model outperforms the state-of-the-art next POI recommendation methods.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering – WISE 2017 - 18th International Conference, Proceedings
EditorsLu Chen, Athman Bouguettaya, Andrey Klimenko, Fedor Dzerzhinskiy, Stanislav V. Klimenko, Xiangliang Zhang, Qing Li, Yunjun Gao, Weijia Jia
Number of pages15
ISBN (Print)9783319687827
StatePublished - 2017
Event18th International Conference on Web Information Systems Engineering, WISE 2017 - Puschino, Russian Federation
Duration: Oct 7 2017Oct 11 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10569 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th International Conference on Web Information Systems Engineering, WISE 2017
Country/TerritoryRussian Federation


  • Metric embedding
  • Next POI recommendation
  • Social relations influence


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