A Cohesive Structure Based Bipartite Graph Analytics System

Wang, K; Hu, Y; Lin, X; Zhang, W; Qin, L; Zhang, Y

A Cohesive Structure Based Bipartite Graph Analytics System

Wang, K Hu, Y Lin, X Zhang, W Qin, L Zhang, Y

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Publisher:: ACM
Publication Type:: Conference Proceeding
Citation:: International Conference on Information and Knowledge Management, Proceedings, 2021, pp. 4799-4803
Issue Date:: 2021-10-26

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Field	Value	Language
dc.contributor.author	Wang, K
dc.contributor.author	Hu, Y
dc.contributor.author	Lin, X
dc.contributor.author	Zhang, W
dc.contributor.author	Qin, L
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-2674-1638
dc.date.accessioned	2021-12-01T23:27:10Z
dc.date.available	2021-12-01T23:27:10Z
dc.date.issued	2021-10-26
dc.identifier.citation	International Conference on Information and Knowledge Management, Proceedings, 2021, pp. 4799-4803
dc.identifier.isbn	9781450384469
dc.identifier.uri	http://hdl.handle.net/10453/152015
dc.description.abstract	Bipartite graphs arise naturally when modeling two different types of entities such as user-item, author-paper, and director-board. In recent years, driven by numerous real-world applications in these networks, mining cohesive structures in bipartite graphs becomes a popular research topic. In this paper, we propose the first cohesive-structure-based bipartite graph analytics system, CohBGA. The key innovative features of our system are as follows. Firstly, we involve several cohesive-structure-based models and statistics in our system to analyze bipartite graphs at different levels of granularity. Secondly, CohBGA has a user-friendly and interactive visual interface with various functional tools to meet users' diverse query requirements. Thirdly, we implement state-of-the-art algorithms in CohBGA to support efficient query processing. Furthermore, as a generic framework is designed in CohBGA, CohBGA is going to be an open-source bipartite graph analytics platform that allows researchers to evaluate the effectiveness of more cohesive-structure-based models and algorithms for bipartite graphs.
dc.language	en
dc.publisher	ACM
dc.relation	http://purl.org/au-research/grants/arc/FT170100128
dc.relation	http://purl.org/au-research/grants/arc/DP210101393
dc.relation.ispartof	International Conference on Information and Knowledge Management, Proceedings
dc.relation.ispartof	CIKM '21: The 30th ACM International Conference on Information and Knowledge Management
dc.relation.isbasedon	10.1145/3459637.3481963
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	A Cohesive Structure Based Bipartite Graph Analytics System
dc.type	Conference Proceeding
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/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2021-12-01T23:27:08Z
pubs.publication-status	Published

Abstract:

Bipartite graphs arise naturally when modeling two different types of entities such as user-item, author-paper, and director-board. In recent years, driven by numerous real-world applications in these networks, mining cohesive structures in bipartite graphs becomes a popular research topic. In this paper, we propose the first cohesive-structure-based bipartite graph analytics system, CohBGA. The key innovative features of our system are as follows. Firstly, we involve several cohesive-structure-based models and statistics in our system to analyze bipartite graphs at different levels of granularity. Secondly, CohBGA has a user-friendly and interactive visual interface with various functional tools to meet users' diverse query requirements. Thirdly, we implement state-of-the-art algorithms in CohBGA to support efficient query processing. Furthermore, as a generic framework is designed in CohBGA, CohBGA is going to be an open-source bipartite graph analytics platform that allows researchers to evaluate the effectiveness of more cohesive-structure-based models and algorithms for bipartite graphs.

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http://hdl.handle.net/10453/152015