Research Article
An Improved Linear Threshold Model
2 downloads
@INPROCEEDINGS{10.1007/978-3-030-63941-9_25, author={Xiaohong Zhang and Nanqun He and Kai Qian and Wanquan Yang and Jianji Ren}, title={An Improved Linear Threshold Model}, proceedings={6GN for Future Wireless Networks. Third EAI International Conference, 6GN 2020, Tianjin, China, August 15-16, 2020, Proceedings}, proceedings_a={6GN}, year={2021}, month={1}, keywords={Linear threshold model Performance Influence maximization Convergence speed}, doi={10.1007/978-3-030-63941-9_25} }- Xiaohong Zhang
Nanqun He
Kai Qian
Wanquan Yang
Jianji Ren
Year: 2021
An Improved Linear Threshold Model
6GN
Springer
DOI: 10.1007/978-3-030-63941-9_25
Abstract
Linear threshold model is one of the widely used diffusion models in influence maximization problem. It simulates influence spread by activating nodes for an iterative way. However, the way it makes activation decisions limits the convergence speed of itself. In this paper, an improvement is proposed to speed up the convergence of Linear threshold model. The improvement makes activation decisions with one step ahead considering the nodes which will be activated soon. To assist in activation decision making, the improvement introduces a new state and updates state transition rules. The experiment results verify the performance and efficiency of the improvement.
Copyright © 2020–2025 ICST
