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.
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Notes
Such relation can be either a “friend” relation or a more intimate acquaintance relation, depending on the nature of the group event in a GSGQ service.
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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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Zhu, Q., Hu, H., Xu, C. et al. Geo-social group queries with minimum acquaintance constraints. The VLDB Journal 26, 709–727 (2017). https://doi.org/10.1007/s00778-017-0473-6
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DOI: https://doi.org/10.1007/s00778-017-0473-6