Alleviating the over-smoothing of graph neural computing by a data augmentation strategy with entropy preservation
X Liu, D Sun, W Wei - Pattern Recognition, 2022 - Elsevier
Abstract The Graph Convolutional Networks (GCN) proposed by Kipf and Welling is an
effective model to improve semi-supervised learning of pattern recognition, but faces the …
effective model to improve semi-supervised learning of pattern recognition, but faces the …
Discovering community structure in social networks based on the synergy of label propagation and simulated annealing
Community detection is one of the critical research areas in the analysis of complex
networks. Numerous algorithms have been devised for this purpose. Despite advances in …
networks. Numerous algorithms have been devised for this purpose. Despite advances in …
Community detection in multiplex networks by deep structure-preserving non-negative matrix factorization
Q Zhou, W Zhu, H Chen, B Peng - Applied Intelligence, 2025 - Springer
Multiplex networks convey more valuable information than single-layer networks; thus,
performing the community detection task involving these networks has become a subject of …
performing the community detection task involving these networks has become a subject of …
A new overlapping community detection algorithm based on similarity of neighbors in complex networks
P Cetin, S Emrah Amrahov - Kybernetika, 2022 - dml.cz
Community detection algorithms help us improve the management of complex networks and
provide a clean sight of them. We can encounter complex networks in various fields such as …
provide a clean sight of them. We can encounter complex networks in various fields such as …
A multi-objective optimization approach for overlapping dynamic community detection
Community detection is a valuable tool for studying the function and dynamic structure of
most real-world networks. Existing techniques either concentrate on the network's …
most real-world networks. Existing techniques either concentrate on the network's …
A motif-based probabilistic approach for community detection in complex networks
H Hajibabaei, V Seydi, A Koochari - Journal of Intelligent Information …, 2024 - Springer
Community detection in complex networks is an important task for discovering hidden
information in network analysis. Neighborhood density between nodes is one of the …
information in network analysis. Neighborhood density between nodes is one of the …
Exhaustive exploitation of local seeding algorithms for community detection in a unified manner
Community detection is an essential task in network analysis and is challenging due to the
rapid growth of network scales. Recently, discovering communities from the local …
rapid growth of network scales. Recently, discovering communities from the local …
Multiscale Community Detection using a Label Propagation-based Clustering Method in Complex Networks
X Zheng, D Xing, K Chen, J Zhao, Y Lu - IEEE Access, 2023 - ieeexplore.ieee.org
Multiscale community detection algorithms can reveal the hierarchy of complex networks.
However, the existing algorithms are unable to realize full-resolution community detection …
However, the existing algorithms are unable to realize full-resolution community detection …
A multi-label propagation algorithm with the double-layer filtering strategy for overlapping community detection
S Yang, J Cao - IEEE Access, 2022 - ieeexplore.ieee.org
Overlapping community structures are universal in complex networks. Multi-label
propagation approach, as a method for detecting overlapping community, has been …
propagation approach, as a method for detecting overlapping community, has been …
Detecting Overlapping Communities in Complex Networks: An Evolutionary Label Propagation Approach
A challenging issue in complex network analysis is overlapping community detection, which
has attracted many studies. Label Propagation Algorithm (LPA) is one of the famous studies …
has attracted many studies. Label Propagation Algorithm (LPA) is one of the famous studies …