Who should be invited to my party: A size-constrained k-core problem in social networks

In this paper, we investigate the problem of a size-constrained k-core group query (SCCGQ) in social networks, taking both user closeness and network topology into consideration. More specifically, SCCGQ intends to find a group of h users that has the highest social closeness while being a k-core. S...

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Main Authors: MA, Yu-Liang, YUAN, Ye, ZHU, Feida, WANG, Guo-Ren, XIAO, Jing, WANG, Jian-Zong
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Language:English
Published: Institutional Knowledge at Singapore Management University 2019
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Online Access:https://ink.library.smu.edu.sg/sis_research/4841
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spelling sg-smu-ink.sis_research-58442020-01-16T09:18:03Z Who should be invited to my party: A size-constrained k-core problem in social networks MA, Yu-Liang YUAN, Ye ZHU, Feida WANG, Guo-Ren XIAO, Jing WANG, Jian-Zong In this paper, we investigate the problem of a size-constrained k-core group query (SCCGQ) in social networks, taking both user closeness and network topology into consideration. More specifically, SCCGQ intends to find a group of h users that has the highest social closeness while being a k-core. SCCGQ can be widely applied to event planning, task assignment, social analysis, and many other fields. In contrast to existing work on the k-core detection problem, which aims to find a k-core in a social network, SCCGQ not only focuses on k-core detection but also takes size constraints into consideration. Although the conventional k-core detection problem can be solved in linear time, SCCGQ has a higher complexity. To solve the problem of SCCGQ, we propose a Blast Scatter (BS) algorithm, which appoints the query node as the center to begin outward expansions via breadth search. In each outward expansion, BS finds a new center through a greedy strategy and then selects multiple neighbors of the center. To speed up the BS algorithm, we propose an advanced search algorithm, called Bounded Extension (BE). Specifically, BE combines an effective social distance pruning strategy and a tight upper bound of social closeness to prune the search space considerably. In addition, we propose an offline social-aware index to accelerate the query processing. Finally, our experimental results demonstrate the efficiency and effectiveness of our proposed algorithms on large real-world social networks. 2019-01-18T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/4841 info:doi/10.1007/s11390-019-1905-0 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Theory and Algorithms
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Theory and Algorithms
spellingShingle Theory and Algorithms
MA, Yu-Liang
YUAN, Ye
ZHU, Feida
WANG, Guo-Ren
XIAO, Jing
WANG, Jian-Zong
Who should be invited to my party: A size-constrained k-core problem in social networks
description In this paper, we investigate the problem of a size-constrained k-core group query (SCCGQ) in social networks, taking both user closeness and network topology into consideration. More specifically, SCCGQ intends to find a group of h users that has the highest social closeness while being a k-core. SCCGQ can be widely applied to event planning, task assignment, social analysis, and many other fields. In contrast to existing work on the k-core detection problem, which aims to find a k-core in a social network, SCCGQ not only focuses on k-core detection but also takes size constraints into consideration. Although the conventional k-core detection problem can be solved in linear time, SCCGQ has a higher complexity. To solve the problem of SCCGQ, we propose a Blast Scatter (BS) algorithm, which appoints the query node as the center to begin outward expansions via breadth search. In each outward expansion, BS finds a new center through a greedy strategy and then selects multiple neighbors of the center. To speed up the BS algorithm, we propose an advanced search algorithm, called Bounded Extension (BE). Specifically, BE combines an effective social distance pruning strategy and a tight upper bound of social closeness to prune the search space considerably. In addition, we propose an offline social-aware index to accelerate the query processing. Finally, our experimental results demonstrate the efficiency and effectiveness of our proposed algorithms on large real-world social networks.
format text
author MA, Yu-Liang
YUAN, Ye
ZHU, Feida
WANG, Guo-Ren
XIAO, Jing
WANG, Jian-Zong
author_facet MA, Yu-Liang
YUAN, Ye
ZHU, Feida
WANG, Guo-Ren
XIAO, Jing
WANG, Jian-Zong
author_sort MA, Yu-Liang
title Who should be invited to my party: A size-constrained k-core problem in social networks
title_short Who should be invited to my party: A size-constrained k-core problem in social networks
title_full Who should be invited to my party: A size-constrained k-core problem in social networks
title_fullStr Who should be invited to my party: A size-constrained k-core problem in social networks
title_full_unstemmed Who should be invited to my party: A size-constrained k-core problem in social networks
title_sort who should be invited to my party: a size-constrained k-core problem in social networks
publisher Institutional Knowledge at Singapore Management University
publishDate 2019
url https://ink.library.smu.edu.sg/sis_research/4841
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