Jianxi Fan
Biographic Data
| ID | 10054002 |
|---|---|
| NAME | Jianxi Fan |
| GIVEN NAMES | Jianxi |
| FAMILY NAME | Fan |
| SIGNATURE | FAN J |
| AFFILIATIONS | Soochow University |
| ORCID | 0000-0002-7055-5891 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Fairness-Aware Competitive Bidding Influence Maximization in Social Networks
Competitive influence maximization (CIM) has been studied for years due to its wide application in many domains. Most current studies primarily focus on the microlevel optimization by designing policies for one competitor to defeat its opponents. Furthermore, current studies ignore the fact that many influential nodes have their own starting prices, which may lead to inefficient budget allocation. In this article, we propose a novel competitive b…
Secure Edge-Aided Computations for Social Internet-of-Things Systems
Devices in the Internet-of-Things (IoT) are networked and perform massive computations to support various social IoT systems. Applications in social IoT systems often involve complicated computations that are out of the computation capacity of some resource-constrained IoT devices. Thus, how to enable resource-constrained IoT devices to accomplish complex computations efficiently and securely is of significant importance. To address this problem,…
No prominent works on this page.
Secure Edge-Aided Computations for Social Internet-of-Things Systems
Devices in the Internet-of-Things (IoT) are networked and perform massive computations to support various social IoT systems. Applications in social IoT systems often involve complicated computations that are out of the computation capacity of some resource-constrained IoT devices. Thus, how to enable resource-constrained IoT devices to accomplish complex computations efficiently and securely is of significant importance. To address this problem,…
Fairness-Aware Competitive Bidding Influence Maximization in Social Networks
Competitive influence maximization (CIM) has been studied for years due to its wide application in many domains. Most current studies primarily focus on the microlevel optimization by designing policies for one competitor to defeat its opponents. Furthermore, current studies ignore the fact that many influential nodes have their own starting prices, which may lead to inefficient budget allocation. In this article, we propose a novel competitive b…
Computer Science (2 works) · Algorithm (1 works) · Artificial Intelligence (1 works) · Bidding (1 works) · Business (1 works) · Chaos-based Image/Signal Encryption (1 works) · Cloud computing (1 works) · Competitor analysis (1 works) · Complex Network Analysis Techniques (1 works) · Computation (1 works)