A comprehensive survey on community detection with deep learning
Detecting a community in a network is a matter of discerning the distinct features and
connections of a group of members that are different from those in other communities. The …
connections of a group of members that are different from those in other communities. The …
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 …
An improved Harris Hawks optimization algorithm with multi-strategy for community detection in social network
FS Gharehchopogh - Journal of Bionic Engineering, 2023 - Springer
The purpose of community detection in complex networks is to identify the structural location
of nodes. Complex network methods are usually graphical, with graph nodes representing …
of nodes. Complex network methods are usually graphical, with graph nodes representing …
A community detection algorithm based on graph compression for large-scale social networks
X Zhao, J Liang, J Wang - Information Sciences, 2021 - Elsevier
Uncovering the underlying community structure of a social network is an important task in
social network analysis. To solve this problem, many community detection algorithms for the …
social network analysis. To solve this problem, many community detection algorithms for the …
A survey of malware analysis using community detection algorithms
In recent years, we have witnessed an overwhelming and fast proliferation of different types
of malware targeting organizations and individuals, which considerably increased the time …
of malware targeting organizations and individuals, which considerably increased the time …
Continuous influence-based community partition for social networks
Community partition is of great importance in social networks because of the rapid
increasing network scale, data and applications. We consider the community partition …
increasing network scale, data and applications. We consider the community partition …
[HTML][HTML] A new attributed graph clustering by using label propagation in complex networks
The diffusion method is one of the main methods of community detection in complex
networks. In this method, the use of the concept that diffusion within the nodes that are …
networks. In this method, the use of the concept that diffusion within the nodes that are …
Unsupervised learning for community detection in attributed networks based on graph convolutional network
X Wang, J Li, L Yang, H Mi - Neurocomputing, 2021 - Elsevier
Community detection has emerged during the last decade as one of the most challenging
problems in network science, which has been revisited with network representation learning …
problems in network science, which has been revisited with network representation learning …
LSMD: A fast and robust local community detection starting from low degree nodes in social networks
Community detection is an appropriate approach for discovering and understanding the
structure and hidden information in complex networks One of the most critical issues in the …
structure and hidden information in complex networks One of the most critical issues in the …
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 …