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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection

February 1, 2023

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Authors

Ling Huang

Sun Yat-sen University


Hong-Yang Chao

Sun Yat-sen University


Quangqiang Xie

Guangdong University of Technology


DOI:

10.1609/aaai.v34i01.5340


Abstract:

In the past few years, higher-order community detection has drawn an increasing amount of attention. Compared with the lower-order approaches that rely on the connectivity pattern of individual nodes and edges, the higher-order approaches discover communities by leveraging the higher-order connectivity pattern via constructing a motif-based hypergraph. Despite success in capturing the building blocks of complex networks, recent study has shown that the higher-order approaches unavoidably suffer from the hypergraph fragmentation issue. Although an edge enhancement strategy has been designed previously to address this issue, adding additional edges may corrupt the original lower-order connectivity pattern. To this end, this paper defines a new problem of community detection, namely hybrid-order community detection, which aims to discover communities by simultaneously leveraging the lower-order connectivity pattern and the higherorder connectivity pattern. For addressing this new problem, a new Micro-unit Modularity (MuMod) approach is designed. The basic idea lies in constructing a micro-unit connection network, where both of the lower-order connectivity pattern and the higher-order connectivity pattern are utilized. And then a new micro-unit modularity model is proposed for generating the micro-unit groups, from which the overlapping community structure of the original network can be derived. Extensive experiments are conducted on five real-world networks. Comparison results with twelve existing approaches confirm the effectiveness of the proposed method.

Topics: AAAI

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HOW TO CITE:

Ling Huang||Hong-Yang Chao||Quangqiang Xie MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection Proceedings of the AAAI Conference on Artificial Intelligence (2020) 107-114.

Ling Huang||Hong-Yang Chao||Quangqiang Xie MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection AAAI 2020, 107-114.

Ling Huang||Hong-Yang Chao||Quangqiang Xie (2020). MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection. Proceedings of the AAAI Conference on Artificial Intelligence, 107-114.

Ling Huang||Hong-Yang Chao||Quangqiang Xie. MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.107-114.

Ling Huang||Hong-Yang Chao||Quangqiang Xie. 2020. MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection. "Proceedings of the AAAI Conference on Artificial Intelligence". 107-114.

Ling Huang||Hong-Yang Chao||Quangqiang Xie. (2020) "MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection", Proceedings of the AAAI Conference on Artificial Intelligence, p.107-114

Ling Huang||Hong-Yang Chao||Quangqiang Xie, "MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection", AAAI, p.107-114, 2020.

Ling Huang||Hong-Yang Chao||Quangqiang Xie. "MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.107-114.

Ling Huang||Hong-Yang Chao||Quangqiang Xie. "MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 107-114.

Ling Huang||Hong-Yang Chao||Quangqiang Xie. MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection. AAAI[Internet]. 2020[cited 2023]; 107-114.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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