A survey of community detection approaches: From statistical modeling to deep learning

D **, Z Yu, P Jiao, S Pan, D He, J Wu… - … on Knowledge and …, 2021 - ieeexplore.ieee.org
Community detection, a fundamental task for network analysis, aims to partition a network
into multiple sub-structures to help reveal their latent functions. Community detection has …

Community detection algorithms in healthcare applications: A systematic review

M Rostami, M Oussalah, K Berahmand… - IEEE Access, 2023 - ieeexplore.ieee.org
Over the past few years, the number and volume of data sources in healthcare databases
has grown exponentially. Analyzing these voluminous medical data is both opportunity and …

Graph regularized nonnegative matrix factorization for community detection in attributed networks

K Berahmand, M Mohammadi… - … on Network Science …, 2022 - ieeexplore.ieee.org
Community detection has become an important research topic in machine learning due to
the proliferation of network data. However, most existing methods have been developed …

Symmetric nonnegative matrix factorization-based community detection models and their convergence analysis

X Luo, Z Liu, L **, Y Zhou… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Community detection is a popular yet thorny issue in social network analysis. A symmetric
and nonnegative matrix factorization (SNMF) model based on a nonnegative multiplicative …

An alternating-direction-method of multipliers-incorporated approach to symmetric non-negative latent factor analysis

X Luo, Y Zhong, Z Wang, M Li - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
Large-scale undirected weighted networks are frequently encountered in big-data-related
applications concerning interactions among a large unique set of entities. Such a network …

A survey of community detection in complex networks using nonnegative matrix factorization

C He, X Fei, Q Cheng, H Li, Z Hu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
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 …

Symmetry and graph bi-regularized non-negative matrix factorization for precise community detection

Z Liu, X Luo, M Zhou - IEEE Transactions on Automation …, 2023 - ieeexplore.ieee.org
Community is a fundamental and highly desired pattern in a Large-scale Undirected
Network (LUN). Community detection is a vital issue when LUN representation learning is …

Highly-accurate community detection via pointwise mutual information-incorporated symmetric non-negative matrix factorization

X Luo, Z Liu, M Shang, J Lou… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Community detection, aiming at determining correct affiliation of each node in a network, is a
critical task of complex network analysis. Owing to its high efficiency, Symmetric and Non …

Customer segmentation using online platforms: isolating behavioral and demographic segments for persona creation via aggregated user data

J An, H Kwak, S Jung, J Salminen… - Social Network Analysis …, 2018 - Springer
We propose a novel approach for isolating customer segments using online customer data
for products that are distributed via online social media platforms. We use non-negative …

Semisupervised adaptive symmetric non-negative matrix factorization

Y Jia, H Liu, J Hou, S Kwong - IEEE transactions on cybernetics, 2020 - ieeexplore.ieee.org
As a variant of non-negative matrix factorization (NMF), symmetric NMF (SymNMF) can
generate the clustering result without additional post-processing, by decomposing a …