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2016 IEEE 32nd International Conference on Data Engineering (ICDE) (2016)
Helsinki, Finland
May 16, 2016 to May 20, 2016
ISBN: 978-1-5090-2020-1
pp: 1510-1511
Yafei Li , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, China
Rui Chen , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, China
Jianliang Xu , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, China
Qiao Huang , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, China
Haibo Hu , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, China
Byron Choi , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, China
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.
INDEX TERMS
Social network services, Collaboration, Algorithm design and analysis, Indexes, Computer science, Electronic mail, Query processing
CITATION

Y. Li, R. Chen, J. Xu, Q. Huang, H. Hu and B. Choi, "Geo-Social K-Cover Group queries for collaborative spatial computing," 2016 IEEE 32nd International Conference on Data Engineering (ICDE), Helsinki, Finland, 2016, pp. 1510-1511.
doi:10.1109/ICDE.2016.7498399
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