虚假信息检测中Bayes模型应用:技术与研究进展

Applications of Bayesian Model in Disinformation Detection:Key Technologies and Progress

为了总结分析Bayes模型在虚假信息检测中的应用研究现状及发展趋势,本文综述了虚假信息检测中的Bayes模型应用研究。运用系统性综述研究方法,在确定虚假信息定义及主要类型基础上,依据信息特征将虚假信息检测分为虚假信息发布者、内容及场景模型等3类,分别阐述了Bayes模型在上述模型中应用的关键技术原理及主要方式,并结合虚假图像、视频类信息检测问题,提出了Bayes模型应用于虚假信息检测中存在的关键技术挑战、可能的研究机会与技术思路。本文结果与结论为虚假信息检测技术相关研究提供了借鉴和参考。

In order to summarize and analyze the status and progress of the applications of Bayesian model in disinformation detection,this paper reviewed related studies using systematic survey method.Definition and categories of disinformation was proposed firstly.And then disinformation detection was decomposed to models based on information source,contents and contexts according to selected features.Key technologies and main ways of Bayesian model applications in disinformation detection were reviewed,and then main challenges,chances and technique routes were given combined with image and video disinformation detection.The results and conclusions provide reference for disinformation detection in practice and research.