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

Yafei Li; Rui CHEN; Jianliang XU; Qiao Huang; Haibo HU; Koon Kau CHOI

doi:10.1109/ICDE.2016.7498399

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

Yafei Li, Rui CHEN, Jianliang XU, Qiao Huang, Haibo HU, Koon Kau CHOI

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

8 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 language	English
Title of host publication	2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016
Publisher	IEEE
Pages	1510-1511
Number of pages	2
ISBN (Electronic)	9781509020195
DOIs	https://doi.org/10.1109/ICDE.2016.7498399
Publication status	Published - 22 Jun 2016
Event	32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland Duration: 16 May 2016 → 20 May 2016

Publication series

Name	2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016

Conference

Conference	32nd IEEE International Conference on Data Engineering, ICDE 2016
Country/Territory	Finland
City	Helsinki
Period	16/05/16 → 20/05/16

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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10.1109/ICDE.2016.7498399

Cite this

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title = "Geo-Social K-Cover Group queries for collaborative spatial computing",

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.",

author = "Yafei Li and Rui CHEN and Jianliang XU and Qiao Huang and Haibo HU and CHOI, {Koon Kau}",

year = "2016",

month = jun,

day = "22",

doi = "10.1109/ICDE.2016.7498399",

language = "English",

series = "2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016",

publisher = "IEEE",

pages = "1510--1511",

booktitle = "2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016",

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note = "32nd IEEE International Conference on Data Engineering, ICDE 2016 ; Conference date: 16-05-2016 Through 20-05-2016",

}

Li, Y, CHEN, R, XU, J, Huang, Q, HU, H & CHOI, KK 2016, Geo-Social K-Cover Group queries for collaborative spatial computing. in 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016., 7498399, 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016, IEEE, pp. 1510-1511, 32nd IEEE International Conference on Data Engineering, ICDE 2016, Helsinki, Finland, 16/05/16. https://doi.org/10.1109/ICDE.2016.7498399

Geo-Social K-Cover Group queries for collaborative spatial computing. / Li, Yafei; CHEN, Rui; XU, Jianliang et al.
2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016. IEEE, 2016. p. 1510-1511 7498399 (2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Geo-Social K-Cover Group queries for collaborative spatial computing

AU - Li, Yafei

AU - CHEN, Rui

AU - XU, Jianliang

AU - Huang, Qiao

AU - HU, Haibo

AU - CHOI, Koon Kau

PY - 2016/6/22

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AB - 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.

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

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