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Updated: Jul 25, 2025

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
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Published on: May 31, 2019

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基于深度强化学习的方法来减少谣言在社交网络中的影响

Jiajian Jiang1, Xiaoliang Chen1,2, Zexia Huang1

  • 1School of Computer and Software Engineering, Xihua University, Chengdu, 610039 People's Republic of China.

Applied intelligence (Dordrecht, Netherlands)
|June 26, 2023
PubMed
概括

这项研究引入了一种动态方法,以尽量减少社交网络上恶意谣言的传播. 一种新的深度强化学习策略,RLDB,有效地识别用户以阻止,优于传统方法.

关键词:
深度Q网络是一个深度Q网络.深度强化学习的学习.在线社交网络 在线社交网络传言影响最小化,减少传言的影响.

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