文章摘要
刘建强,卢为党,黄国兴,马宁.基于深度学习的互联网虚假信息识别研究[J].情报工程,2022,8(5):086-099
基于深度学习的互联网虚假信息识别研究
Identifying Internet Fake Information based on Deep Learning
  
DOI:10.3772/j.issn.2095-915X.2022.05.008
中文关键词: 案例分析;互联网虚假信息;识别;深度学习
英文关键词: Case study; Internet fake information; identification; deep learning
基金项目:
作者单位
刘建强 1. 军事科学院战争研究院 北京 100091; 
卢为党 2. 浙江工业大学信息工程学院 杭州 310023 
黄国兴 2. 浙江工业大学信息工程学院 杭州 310023 
马宁 1. 军事科学院战争研究院 北京 100091; 
摘要点击次数: 88
全文下载次数: 83
中文摘要:
      [ 目的 / 意义 ] 随着互联网技术的高速发展,虚假信息混杂成为近些年来在高新科技领域凸显出的网络舆情样式。虚假信息可作为影响科技战略态势的重要“武器”,会阻碍我国正确高效获取有价值的各类数据,从而给国家和社会造成不可估量的损失。[ 方法 / 过程 ] 本文针对互联网虚假信息的基本概念进行梳理,并结合近年相关研究工作,提出一套针对虚假信息识别的软件平台设计。同时,为提升软件平台虚假信息识别的准确度、加快算法收敛,提出一种基于生成对抗网络的虚假信息筛选算法。[ 结果 / 结论 ] 提出的虚假信息识别平台有效提升了信息识别的精准度。
英文摘要:
      [Purpose/Significance] With the rapid development of Internet technology, the mixing of fake information has become a pattern of network public opinion highlighted in the field of high-tech in recent years. Fake information can be used as an important “weapon” to affect the strategic situation of science and technology, which will prevent my country from obtaining various types of valuable data correctly and efficiently, thereby causing immeasurable losses to the country and society. [Methods/Processes] This paper sorts out the basic concepts of Internet fake information, and proposes a set of software platform design for fake information identification based on related research work in recent years. At the same time, in order to improve the accuracy of fake information recognition on the software platform and speed up the algorithm convergence, a fake information screening algorithm based on generative adversarial network is proposed. [Results/Conclusions] The experimental results show that the proposed fake information identification platform effectively improves the accuracy of information identification
查看全文   查看/发表评论  下载PDF阅读器
关闭

分享按钮