首页> 外文期刊>Programming and Computer Software >Machine Learning Methods for Detecting and Monitoring Extremist Information on the Internet
【24h】

Machine Learning Methods for Detecting and Monitoring Extremist Information on the Internet

机译:用于在互联网上检测和监视极端信息的机器学习方法

获取原文
获取原文并翻译 | 示例

摘要

In this paper, we employ machine learning methods to solve the problem of countering terrorism and extremism by using information from the Internet. This problem involves retrieving electronic messages, documents, and web resources that potentially contain information of terrorist or extremist nature, identifying the structure of user groups and online communities that disseminate this information, monitoring and modeling information flows in these communities, as well as assessing threats and predicting risks based on monitoring results. We propose some original language-independent algorithms for pattern-based information retrieval, thematic modeling, and prediction of message flow characteristics, as well as assessment and prediction of potential risk coming from members of online communities by using data on the structure of relations in these communities, which makes it possible to detect potentially dangerous users even without full access to the content they distribute, e.g., through private channels and chat rooms.
机译:在本文中,我们采用机器学习方法,通过利用来自互联网的信息来解决反恐和极端主义的问题。此问题涉及检索可能包含恐怖分子或极端主义性质信息的电子消息,文档和网络资源,确定散布此信息的用户群体和在线社区的结构,监视和建模这些社区中的信息流,以及评估威胁并根据监测结果预测风险。我们提出了一些独立于语言的原始算法,用于基于模式的信息检索,主题建模和消息流特征的预测,以及通过使用这些关系结构上的数据来评估和预测来自在线社区成员的潜在风险社区,即使没有完全访问他们分发的内容的权限,例如通过私人渠道和聊天室,也可以检测潜在的危险用户。

著录项

  • 来源
    《Programming and Computer Software》 |2019年第3期|99-115|共17页
  • 作者单位

    Moscow MV Lomonosov State Univ, Fac Computat Math & Cybernet, Moscow 119899, Russia;

    Moscow MV Lomonosov State Univ, Fac Computat Math & Cybernet, Moscow 119899, Russia;

    Moscow MV Lomonosov State Univ, Fac Computat Math & Cybernet, Moscow 119899, Russia;

    Moscow MV Lomonosov State Univ, Fac Computat Math & Cybernet, Moscow 119899, Russia;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号