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The VLDB Journal

, Volume 26, Issue 5, pp 709–727 | Cite as

Geo-social group queries with minimum acquaintance constraints

  • Qijun Zhu
  • Haibo Hu
  • Cheng Xu
  • Jianliang Xu
  • Wang-Chien Lee
Regular Paper

Abstract

The prosperity of location-based social networking has paved the way for new applications of group-based activity planning and marketing. While such applications heavily rely on geo-social group queries (GSGQs), existing studies fail to produce a cohesive group in terms of user acquaintance. In this paper, we propose a new family of GSGQs with minimum acquaintance constraints. They are more appealing to users as they guarantee a worst-case acquaintance level in the result group. For efficient processing of GSGQs on large location-based social networks, we devise two social-aware spatial index structures, namely SaR-tree and SaR*-tree. The latter improves on the former by considering both spatial and social distances when clustering objects. Based on SaR-tree and SaR*-tree, novel algorithms are developed to process various GSGQs. Extensive experiments on real datasets Gowalla and Twitter show that our proposed methods substantially outperform the baseline algorithms under various system settings.

Keywords

Location-based services Geo-social networks Spatial queries Nearest neighbor queries 

Notes

Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos.: 61572413 and U1636205), and Research Grants Council, Hong Kong SAR, China, under Projects 12244916, 12201615, 12202414, 12200914, 15238116, and C1008-16G.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceHong Kong Baptist UniversityKowloon TongHong Kong
  2. 2.Department of Electronic and Information EngineeringHong Kong Polytechnic UniversityHung HomHong Kong
  3. 3.Department of Computer Science and EngineeringPennsylvania State UniversityUniversity ParkUSA

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