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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 |
Issue Date: | Oct-2017 | Source: | VLDB journal, Oct. 2017, v. 26, no. 5, p. 709-727 | 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 |
Publisher: | Springer | Journal: | VLDB journal | ISSN: | 1066-8888 | EISSN: | 0949-877X | DOI: | 10.1007/s00778-017-0473-6 | Rights: | © Springer-Verlag GmbH Germany 2017 This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00778-017-0473-6. |
Appears in Collections: | Journal/Magazine Article |
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Hu_Geo-Social_Group_Queries.pdf | Pre-Published version | 1.15 MB | Adobe PDF | View/Open |
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