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 …
Cryptocurrency transaction network embedding from static and dynamic perspectives: An overview
Cryptocurrency, as a typical application scene of blockchain, has attracted broad interests
from both industrial and academic communities. With its rapid development, the …
from both industrial and academic communities. With its rapid development, 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 …
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 …
Community detection based on directed weighted signed graph convolutional networks
H Cheng, C He, H Liu, X Liu, P Yu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Currently, community detection in signed networks has become a popular research topic
due to the widespread use of signed networks for modeling relationships among entities in …
due to the widespread use of signed networks for modeling relationships among entities in …
Exploiting optimised communities in directed weighted graphs for link prediction
The most developing issue in analysing complex networks and graph mining is link
prediction, which can be studied for both content and structural-based analysis in a social …
prediction, which can be studied for both content and structural-based analysis in a social …
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 …
Multi-constraint non-negative matrix factorization for community detection: orthogonal regular sparse constraint non-negative matrix factorization
Z Chen, Q Xiao, T Leng, Z Zhang, D Pan, Y Liu… - Complex & Intelligent …, 2024 - Springer
Community detection is an important method to analyze the characteristics and structure of
community networks, which can excavate the potential links between nodes and further …
community networks, which can excavate the potential links between nodes and further …
Diagnosis of Overlapping Communities and Coherent Groups Using Structural Centrality based Methodology.
TA Diame, SA Zearah, A Kadeem… - Journal of Intelligent …, 2023 - search.ebscohost.com
Community detection in complex networks has become an important step in understanding
the structure and behaviour of networks in many fields. However, both standard node …
the structure and behaviour of networks in many fields. However, both standard node …
A Fast Local Community Detection Algorithm in Signed Social Networks
S Bakhtar, HA Harutyunyan - 2022 Ninth International …, 2022 - ieeexplore.ieee.org
Recent years have witnessed the rapid growth of social network services and consequently,
research problems investigated in this area. Community detection is one of the most …
research problems investigated in this area. Community detection is one of the most …