An extended self-representation model of complex networks for link prediction
As a fundamental problem in network science, link prediction is both theoretically significant
and practically useful. Many existing link prediction algorithms rely on predefined …
and practically useful. Many existing link prediction algorithms rely on predefined …
A Complex Network Analysis Approach to Bankruptcy Prediction using Company Relational Information-based Drivers
J Zhao, J Ouenniche, J De Smedt - Knowledge-Based Systems, 2024 - Elsevier
Corporate bankruptcy prediction is a long-standing topic of interest for a variety of
stakeholders. Various prediction methodologies have been proposed to achieve more …
stakeholders. Various prediction methodologies have been proposed to achieve more …
TemporalHAN: Hierarchical attention-based heterogeneous temporal network embedding
X Mo, B Wan, R Tang - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Heterogeneous temporal network embedding aims to learn each node of different types of a
heterogeneous temporal network in each snapshot into a low-dimensional vector …
heterogeneous temporal network in each snapshot into a low-dimensional vector …
Identification of Key Nodes in Complex Networks Based on Network Representation Learning
H Zhang, S Zhang, X Xie, T Zhang, G Yu - IEEE Access, 2023 - ieeexplore.ieee.org
Recently, some research has utilized machine learning methods to identify critical nodes in
complex networks. However, existing approaches often lack a comprehensive consideration …
complex networks. However, existing approaches often lack a comprehensive consideration …