Geo-Social K-Cover Group queries for collaborative spatial computing

Yafei Li, Rui Chen, Jianliang Xu, Qiao Huang, Haibo Hu, Byron Choi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

In this paper, we study a new type of Geo-Social K-Cover Group (GSKCG) queries that, given a set of query points and a social network, retrieves a minimum user group in which each user is socially related to at least k other users and the users' associated regions (e.g., familiar regions or service regions) can jointly cover all the query points. Albeit its practical usefulness, the GSKCG query problem is NP-hard. We consequently explore a set of effective pruning strategies to derive an efficient algorithm for finding the optimal solution. Moreover, we design a novel index structure tailored to our problem to further accelerate query processing. Extensive experiments demonstrate that our algorithm achieves desirable performance on real-life datasets.
Original languageEnglish
Title of host publication2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016
PublisherIEEE
Pages1510-1511
Number of pages2
ISBN (Electronic)9781509020195
DOIs
Publication statusPublished - 22 Jun 2016
Externally publishedYes
Event32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland
Duration: 16 May 201620 May 2016

Conference

Conference32nd IEEE International Conference on Data Engineering, ICDE 2016
CountryFinland
CityHelsinki
Period16/05/1620/05/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Graphics and Computer-Aided Design
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

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