Hongchang Chen
Biographic Data
| ID | 10055710 |
|---|---|
| NAME | Hongchang Chen |
| GIVEN NAMES | Hongchang |
| FAMILY NAME | Chen |
| SIGNATURE | CHEN H |
| AFFILIATIONS | National Digital Switching System Engineering and Technological Research Center, Zhengzhou, China |
| ORCID | 0009-0005-0626-9830 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Advancing User Behavior Analysis
In addressing the cold-start problem in individual location prediction, we introduce a novel bilateral-branch network to enhance prediction accuracy specifically for cold-start users, without sacrificing general performance. This network integrates a main-branch that analyzes mobility behavior across all users and a sampling-branch dedicated to cold-start users, both employing a shared encoder to ensure consistent learning of behavioral patterns.…
Cost-Sensitive GNN-Based Imbalanced Learning for Mobile Social Network Fraud Detection
In recent years, the increasing prevalence of mobile social network fraud has led to significant distress and depletion of personal and social wealth, resulting in considerable economic harm. Graph neural networks (GNNs) have emerged as a popular approach to tackle this issue. However, the challenge of graph imbalance, which can greatly impede the effectiveness of GNN-based fraud detection methods, has received little attention in prior research.…
No prominent works on this page.
Cost-Sensitive GNN-Based Imbalanced Learning for Mobile Social Network Fraud Detection
In recent years, the increasing prevalence of mobile social network fraud has led to significant distress and depletion of personal and social wealth, resulting in considerable economic harm. Graph neural networks (GNNs) have emerged as a popular approach to tackle this issue. However, the challenge of graph imbalance, which can greatly impede the effectiveness of GNN-based fraud detection methods, has received little attention in prior research.…
Advancing User Behavior Analysis
In addressing the cold-start problem in individual location prediction, we introduce a novel bilateral-branch network to enhance prediction accuracy specifically for cold-start users, without sacrificing general performance. This network integrates a main-branch that analyzes mobility behavior across all users and a sampling-branch dedicated to cold-start users, both employing a shared encoder to ensure consistent learning of behavioral patterns.…
Computer Science (2 works) · Advanced Graph Neural Networks (1 work) · Artificial Intelligence (1 work) · Computer network (1 work) · Confusion matrix (1 work) · Context-Aware Activity Recognition Systems (1 work) · Data mining (1 work) · Embedding (1 work) · Engineering (1 work) · Graph (1 work)