The rise of nonnegative matrix factorization: algorithms and applications
YT Guo, QQ Li, CS Liang - Information Systems, 2024 - Elsevier
Although nonnegative matrix factorization (NMF) is widely used, some matrix factorization
methods result in misleading results and waste of computing resources due to lack of timely …
methods result in misleading results and waste of computing resources due to lack of timely …
Symmetric nonnegative matrix factorization-based community detection models and their convergence analysis
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 …
and nonnegative matrix factorization (SNMF) model based on a nonnegative multiplicative …
Graph regularized nonnegative matrix factorization for community detection in attributed networks
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 …
the proliferation of network data. However, most existing methods have been developed …
Deep autoencoder-like nonnegative matrix factorization for community detection
Community structure is ubiquitous in real-world complex networks. The task of community
detection over these networks is of paramount importance in a variety of applications …
detection over these networks is of paramount importance in a variety of applications …
A survey of community detection methods in multilayer networks
X Huang, D Chen, T Ren, D Wang - Data Mining and Knowledge …, 2021 - Springer
Community detection is one of the most popular researches in a variety of complex systems,
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …
Highly-accurate community detection via pointwise mutual information-incorporated symmetric non-negative matrix factorization
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 …
critical task of complex network analysis. Owing to its high efficiency, Symmetric and Non …
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 …
Symmetry and graph bi-regularized non-negative matrix factorization for precise community detection
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 …
Network (LUN). Community detection is a vital issue when LUN representation learning is …
A survey about community detection over On-line Social and Heterogeneous Information Networks
Abstract In modern Online Social Networks (OSNs), the need to detect users' communities
based on their interests and social connections has became a more and more important …
based on their interests and social connections has became a more and more important …
Semi-supervised non-negative matrix factorization with dissimilarity and similarity regularization
In this article, we propose a semi-supervised non-negative matrix factorization (NMF) model
by means of elegantly modeling the label information. The proposed model is capable of …
by means of elegantly modeling the label information. The proposed model is capable of …