Deep Reinforcement Learning-Based Approach to Tackle Topic-Aware Influence Maximization

Deep Reinforcement Learning-Based Approach to Tackle Topic-Aware Influence Maximization

Abstract Motivated by the application of viral marketing, the topic-aware influence maximization (TIM) problem has been proposed to identify the most influential users under given topics. In particular, it aims to find k seeds (users) in social network G, such that the seeds can maximize the influen...

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Bibliographic Details
Main Authors: Shan Tian, Songsong Mo, Liwei Wang, Zhiyong Peng
Format: Article
Language:English
Published: SpringerOpen 2020-02-01
Series:Data Science and Engineering
Subjects:
Social network
Influence maximization
Graph embedding
Reinforcement learning
Online Access:https://doi.org/10.1007/s41019-020-00117-1

Internet

https://doi.org/10.1007/s41019-020-00117-1

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