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 …
Community detection in social networks: an in-depth benchmarking study with a procedure-oriented framework
M Wang, C Wang, JX Yu, J Zhang - Proceedings of the VLDB …, 2015 - dl.acm.org
Revealing the latent community structure, which is crucial to understanding the features of
networks, is an important problem in network and graph analysis. During the last decade …
networks, is an important problem in network and graph analysis. During the last decade …
Information granulation-based community detection for social networks
ED Raj, G Manogaran, G Srivastava… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Online social networks (OSNs) have become so popular that it has changed the Internet to a
more collaborative environment. Now, a third of the world's population participates in OSNs …
more collaborative environment. Now, a third of the world's population participates in OSNs …
Community detection in large-scale social networks: state-of-the-art and future directions
Community detection is an important research area in social networks analysis where we
are concerned with discovering the structure of the social network. Detecting communities is …
are concerned with discovering the structure of the social network. Detecting communities is …
High quality, scalable and parallel community detection for large real graphs
A Prat-Pérez, D Dominguez-Sal… - Proceedings of the 23rd …, 2014 - dl.acm.org
Community detection has arisen as one of the most relevant topics in the field of graph
mining, principally for its applications in domains such as social or biological networks …
mining, principally for its applications in domains such as social or biological networks …
Adaptive community detection incorporating topology and content in social networks
In social network analysis, community detection is a basic step to understand the structure,
function and semantics of networks. Some conventional community detection methods may …
function and semantics of networks. Some conventional community detection methods may …
High-performance community detection in social networks using a deep transitive autoencoder
Y Xie, X Wang, D Jiang, R Xu - Information Sciences, 2019 - Elsevier
Community structure is an important characteristic of complex networks. It determines where
important functions of a network are located. Recently, discovering community structure in …
important functions of a network are located. Recently, discovering community structure in …
Enhancing community detection using a network weighting strategy
A community within a network is a group of vertices densely connected to each other but
less connected to the vertices outside. The problem of detecting communities in large …
less connected to the vertices outside. The problem of detecting communities in large …
LED: A fast overlapping communities detection algorithm based on structural clustering
Community detection in social networks is a fundamental task of complex network analysis.
Community is usually regarded as a functional unit. Networks in real world more or less …
Community is usually regarded as a functional unit. Networks in real world more or less …
A deep learning based community detection approach
G Sperlí - Proceedings of the 34th ACM/SIGAPP symposium on …, 2019 - dl.acm.org
Community Detection in On Line Social Networks is a classic feature in networked systems,
from the fields of biology, economics, politics and computer science, as well. This paper …
from the fields of biology, economics, politics and computer science, as well. This paper …