An unsupervised Bayesian neural network for truth discovery in social networks

• Main Authors: Yang, Jielong, Tay, Wee Peng
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Article
• 語言: English
• 出版: 2021
• 主題: Engineering::Electrical and electronic engineering; Truth Discovery; Unsupervised Learning
• 在線閱讀: https://hdl.handle.net/10356/153704

The problem of estimating event truths from conflicting agent opinions in a social network is investigated. An autoencoder learns the complex relationships between event truths, agent reliabilities and agent observations. A Bayesian network model is proposed to guide the learning process by modeling...