Finding maximal stable cores in social networks

Zhou, A; Zhang, F; Yuan, L; Zhang, Y; Lin, X

Finding maximal stable cores in social networks

Zhou, A Zhang, F Yuan, L Zhang, Y

Lin, X

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, 10837 LNCS pp. 224 - 235
Issue Date:: 2018-01-01

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Field	Value	Language
dc.contributor.author	Zhou, A	en_US
dc.contributor.author	Zhang, F	en_US
dc.contributor.author	Yuan, L	en_US
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-2674-1638	en_US
dc.contributor.author	Lin, X	en_US
dc.date.issued	2018-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, 10837 LNCS pp. 224 - 235	en_US
dc.identifier.isbn	9783319920122	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133501
dc.description.abstract	© Springer International Publishing AG, part of Springer Nature 2018. Maximal Stable Cores are a cohesive subgraph on a social network which use both engagement and similarity to identify stable groups of users. The problem is, when given a query user and a similarity threshold, to find all Maximal Stable Cores relative to the user. We propose a baseline algorithm and as the problem is NP-Hard, an improved heuristic algorithm which utilises linear time k-core decomposition. Experiments how that when the two algorithms differ, the improved algorithm significantly outperforms the baseline.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-319-92013-9_18	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Finding maximal stable cores in social networks	en_US
dc.type	Conference Proceeding
utslib.citation.volume	10837 LNCS	en_US
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	10837 LNCS	en_US

Abstract:

© Springer International Publishing AG, part of Springer Nature 2018. Maximal Stable Cores are a cohesive subgraph on a social network which use both engagement and similarity to identify stable groups of users. The problem is, when given a query user and a similarity threshold, to find all Maximal Stable Cores relative to the user. We propose a baseline algorithm and as the problem is NP-Hard, an improved heuristic algorithm which utilises linear time k-core decomposition. Experiments how that when the two algorithms differ, the improved algorithm significantly outperforms the baseline.

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http://hdl.handle.net/10453/133501