Reinforcement Learning-Based Rumor Blocking Approach in Directed Social Networks-Reference-Cited by-同舟云学术

Reinforcement Learning-Based Rumor Blocking Approach in Directed Social Networks

Published:2022-12 Issue:4 Volume:16 Page:6457-6467
ISSN:1932-8184
Container-title:IEEE Systems Journal
language:
Short-container-title:IEEE Systems Journal

Author:

He Qiang¹^ORCID,Lv Yingjie¹,Wang Xingwei²^ORCID,Huang Min³,Cai Yuliang⁴^ORCID

Affiliation:

1. College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China

2. Northeastern University, the State Key Laboratory of Synthetical Automation for Process Industries, College of Computer Science and Engineering, Shenyang, China

3. State Key Laboratory of Synthetical Automation for Process Industries, College of Information Science and Engineering, Northeastern University, Shenyang, China

4. School of Mathematics and Statistics, Liaoning University, Shenyang, China

Funder

LiaoNing Revitalization Talents Program

National Natural Science Foundation of China

Key Project of Natural Science Foundation of China

Major International (Regional) Joint Research Project

Science and Technology Planning Project of Shenyang City

Doctor Startup Foundation of Liaoning Province

Fundamental Research Funds for the Central Universities

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/4267003/9979155/09748868.pdf?arnumber=9748868

Reference49 articles.

1. Random Sample Partition: A Distributed Data Model for Big Data Analysis

2. General Rumor Blocking: An efficient random algorithm with martingale approach

3. On the evolution of random graphs;erdos;Publ Math Inst Hung Acad,1960

4. Statistical mechanics of complex networks

5. Reinforcement-Learning-Based Dynamic Opinion Maximization Framework in Signed Social Networks

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