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A survey of community detection in complex networks using nonnegative matrix factorization
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 …
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
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 …
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
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 …
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 …
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 …
disseminate and acquire knowledge. These communities consist of entities (actual objects …
A high-order proximity-incorporated nonnegative matrix factorization-based community detector
Community describes the functional mechanism of an undirected network, making
community detection a fundamental tool for graph representation learning-related …
community detection a fundamental tool for graph representation learning-related …
Symmetry and nonnegativity-constrained matrix factorization for community detection
Dear Editor, This letter presents a novel symmetry and nonnegativity-constrained matrix
factorization (SNCMF)-based community detection model on undirected networks such as a …
factorization (SNCMF)-based community detection model on undirected networks such as a …
Community detection in graph: An embedding method
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 …
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 …
attention. Among various community detection methods, nonnegative matrix factorization …
Boosting nonnegative matrix factorization based community detection with graph attention auto-encoder
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 …
networks. It has become one of popular research topics in the field of complex networks …