Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75824
Title: Geo-social group queries with minimum acquaintance constraints
Authors: Zhu, QJ
Hu, HB 
Xu, C
Xu, JL
Lee, WC
Keywords: Location-based services
Geo-social networks
Spatial queries
Nearest neighbor queries
Issue Date: 2017
Publisher: Springer
Source: VLDB journal, 2017, v. 26, no. 5, p. 709-727 How to cite?
Journal: VLDB journal 
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.
URI: http://hdl.handle.net/10397/75824
ISSN: 1066-8888
EISSN: 0949-877X
DOI: 10.1007/s00778-017-0473-6
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