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Issue No. 10 - Oct. (2015 vol. 27)
ISSN: 1041-4347
pp: 2729-2742
Yafei Li , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
Rui Chen , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
Jianliang Xu , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
Qiao Huang , College of Computer Science and Technology, Zhejiang University, Hangzhou, China
Haibo Hu , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
Byron Choi , Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
ABSTRACT
With the rapid development of location-aware mobile devices, ubiquitous Internet access and social computing technologies, lots of users’ personal information, such as location data and social data, has been readily accessible from various mobile platforms and online social networks. The convergence of these two types of data, known as geo-social data, has enabled collaborative spatial computing that explicitly combines both location and social factors to answer useful geo-social queries for either business or social good. 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-complete. 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
Silicon, Social network services, Collaboration, Algorithm design and analysis, Indexes, Social factors, Mobile communication
CITATION

Y. Li, R. Chen, J. Xu, Q. Huang, H. Hu and B. Choi, "Geo-Social K-Cover Group Queries for Collaborative Spatial Computing," in IEEE Transactions on Knowledge & Data Engineering, vol. 27, no. 10, pp. 2729-2742, 2015.
doi:10.1109/TKDE.2015.2419663
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