26 citations · 53 across the 5 of their papers we have counts for
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cs.SI2023
Finding Influencers in Complex Networks: An Effective Deep Reinforcement Learning Approach
Changan Liu, Changjun Fan, Zhongzhi Zhang
Maximizing influences in complex networks is a practically important but computationally challenging task for social network analysis, due to its NP- hard nature. Most current appr…
cs.SI2019
Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach
Changjun Fan, Li Zeng, Yuhui Ding +3
Betweenness centrality (BC) is one of the most used centrality measures for network analysis, which seeks to describe the importance of nodes in a network in terms of the fraction…