A survey of community detection in complex networks using nonnegative matrix factorization

C He, X Fei, Q Cheng, H Li, Z Hu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Community detection is one of the popular research topics in the field of complex networks
analysis. It aims to identify communities, represented as cohesive subgroups or clusters …

Symmetry and graph bi-regularized non-negative matrix factorization for precise community detection

Z Liu, X Luo, M Zhou - IEEE Transactions on Automation …, 2023 - ieeexplore.ieee.org
Community is a fundamental and highly desired pattern in a Large-scale Undirected
Network (LUN). Community detection is a vital issue when LUN representation learning is …

A novel method of spectral clustering in attributed networks by constructing parameter-free affinity matrix

K Berahmand, M Mohammadi, A Faroughi… - Cluster …, 2022 - Springer
The most basic and significant issue in complex network analysis is community detection,
which is a branch of machine learning. Most current community detection approaches, only …

A deep semi-supervised community detection based on point-wise mutual information

K Berahmand, Y Li, Y Xu - IEEE Transactions on Computational …, 2023 - ieeexplore.ieee.org
Network clustering is one of the fundamental unsupervised methods of knowledge
discovery. Its goal is to group similar nodes together without supervision or prior knowledge …

Heterogeneous question answering community detection based on graph neural network

Y Wu, Y Fu, J Xu, H Yin, Q Zhou, D Liu - Information Sciences, 2023 - Elsevier
Topic-based communities have gradually become a considerable medium for netizens to
disseminate and acquire knowledge. These communities consist of entities (actual objects …

A high-order proximity-incorporated nonnegative matrix factorization-based community detector

Z Liu, Y Yi, X Luo - IEEE Transactions on Emerging Topics in …, 2023 - ieeexplore.ieee.org
Community describes the functional mechanism of an undirected network, making
community detection a fundamental tool for graph representation learning-related …

Symmetry and nonnegativity-constrained matrix factorization for community detection

Z Liu, G Yuan, X Luo - IEEE/CAA Journal of Automatica Sinica, 2022 - ieeexplore.ieee.org
Dear Editor, This letter presents a novel symmetry and nonnegativity-constrained matrix
factorization (SNCMF)-based community detection model on undirected networks such as a …

Community detection in graph: An embedding method

J Zhu, C Wang, C Gao, F Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In the real world, understanding and discovering community structures of networks are
significant in exploring network behaviors and functions. In addition to the effect of the …

Dual-learning multi-hop nonnegative matrix factorization for community detection

X Bai, B Chen, Z Zhuo - Neural Networks, 2024 - Elsevier
As an important branch of network science, community detection has garnered significant
attention. Among various community detection methods, nonnegative matrix factorization …

Boosting nonnegative matrix factorization based community detection with graph attention auto-encoder

C He, Y Zheng, X Fei, H Li, Z Hu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Community detection is of great help to understand the structures and functions of complex
networks. It has become one of popular research topics in the field of complex networks …