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 …
Social Network Analysis: A Survey on Process, Tools, and Application
Due to the explosive rise of online social networks, social network analysis (SNA) has
emerged as a significant academic field in recent years. Understanding and examining …
emerged as a significant academic field in recent years. Understanding and examining …
Community detection in complex networks by detecting and expanding core nodes through extended local similarity of nodes
K Berahmand, A Bouyer… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
As the community detection is able to facilitate the discovery of hidden information in
complex networks, it has been drawn a lot of attention recently. However, due to the growth …
complex networks, it has been drawn a lot of attention recently. However, due to the growth …
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 …
A three-stage algorithm for local community detection based on the high node importance ranking in social networks
Community detection aims to discover and reveal community structures in complex
networks. Some community detection method is called local methods that only apply local …
networks. Some community detection method is called local methods that only apply local …
Community detection in complex networks with an ambiguous structure using central node based link prediction
Community detection in complex networks has aroused wide attention, since it can find
some useful information hidden in the networks. Many different community detection …
some useful information hidden in the networks. Many different community detection …
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 …
PLDLS: A novel parallel label diffusion and label Selection-based community detection algorithm based on Spark in social networks
Parallel and distributed community detection in large-scale complex networks, such as
social networks, is a challenging task. Parallel and distributed algorithm with high accuracy …
social networks, is a challenging task. Parallel and distributed algorithm with high accuracy …
Analysis of university students' behavior based on a fusion K-means clustering algorithm
W Chang, X Ji, Y Liu, Y Xiao, B Chen, H Liu, S Zhou - Applied Sciences, 2020 - mdpi.com
With the development of big data technology, creating the 'Digital Campus' is a hot issue. For
an increasing amount of data, traditional data mining algorithms are not suitable. The …
an increasing amount of data, traditional data mining algorithms are not suitable. The …
Overlapping community detection based on structural centrality in complex networks
X Wang, G Liu, J Li - IEEE Access, 2017 - ieeexplore.ieee.org
Community structure is an important mesoscale topological characteristic of complex
networks, which is significant for understanding structural features and organizational …
networks, which is significant for understanding structural features and organizational …