Lo-Yao Yeh
Biographic Data
| ID | 10054636 |
|---|---|
| NAME | Lo-Yao Yeh |
| GIVEN NAMES | Lo-Yao |
| FAMILY NAME | Yeh |
| SIGNATURE | YEH -Y |
| AFFILIATIONS | National Central University |
| ORCID | 0000-0002-9764-0455 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Misinformation Detection via LLM-Based Expert Discussion Network
Detecting Targets of Graph Adversarial Attacks With Edge and Feature Perturbations
Graph neural networks (GNNs) enable many novel applications and achieve excellent performance. However, their performance may be significantly degraded by the graph adversarial attacks, which intentionally add small perturbations to the graph. Previous countermeasures usually handle such attacks by enhancing model robustness. However, robust models cannot identify the target nodes of the adversarial attacks, and thus we are unable to pinpoint the…
Learning to Extract Expert Teams in Social Networks
Finding a set of suitable experts with minimized communication overhead to perform a complex task finds a wide spectrum of applications in industry, education, and other scenarios. This class of problems, widely formulated as forming a team of experts in social networks (i.e., team formation problem), is very challenging due to its NP-hardness and has attracted much research attention. Although various effective and elegant algorithms have been p…
Efficient Extraction of Target Users for Package Promotion in Big Social Networks
Package promotion (or product bundling and bundle promotion) is widely adopted as an effective marketing strategy to increase sales, but the social tightness of the users significantly influences their willingness to purchase certain products. However, addressing these two factors simultaneously is not a trivial task because it is critical to properly choose a set of socially tight target users to encourage them to buy the products together (soci…
No prominent works on this page.
Efficient Extraction of Target Users for Package Promotion in Big Social Networks
Package promotion (or product bundling and bundle promotion) is widely adopted as an effective marketing strategy to increase sales, but the social tightness of the users significantly influences their willingness to purchase certain products. However, addressing these two factors simultaneously is not a trivial task because it is critical to properly choose a set of socially tight target users to encourage them to buy the products together (soci…
Learning to Extract Expert Teams in Social Networks
Finding a set of suitable experts with minimized communication overhead to perform a complex task finds a wide spectrum of applications in industry, education, and other scenarios. This class of problems, widely formulated as forming a team of experts in social networks (i.e., team formation problem), is very challenging due to its NP-hardness and has attracted much research attention. Although various effective and elegant algorithms have been p…
Detecting Targets of Graph Adversarial Attacks With Edge and Feature Perturbations
Graph neural networks (GNNs) enable many novel applications and achieve excellent performance. However, their performance may be significantly degraded by the graph adversarial attacks, which intentionally add small perturbations to the graph. Previous countermeasures usually handle such attacks by enhancing model robustness. However, robust models cannot identify the target nodes of the adversarial attacks, and thus we are unable to pinpoint the…
Misinformation Detection via LLM-Based Expert Discussion Network
Computer Science (3 works) · Artificial Intelligence (2 works) · Expert finding and Q&A systems (2 works) · Graph (2 works) · Mathematics (2 works) · Theoretical Computer Science (2 works) · Advanced Graph Neural Networks (1 work) · Adversarial Robustness in Machine Learning (1 work) · Adversarial system (1 work) · Auction Theory and Applications (1 work)