Geo-social group queries with minimum acquaintance constraints

Qijun Zhu, Haibo Hu, Cheng Xu, Jianliang Xu, Wang Chien Lee

Research output: Journal article publicationJournal articleAcademic researchpeer-review

26 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)709-727
Number of pages19
JournalVLDB Journal
Volume26
Issue number5
DOIs
Publication statusPublished - 1 Oct 2017

Keywords

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

ASJC Scopus subject areas

  • Information Systems
  • Hardware and Architecture

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