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首页> 外文会议>IEEE International Conference on Big Data >Extending the Scope of Computational Archival Science: A Case Study on Leveraging Archival and Engineering Approaches to Develop a Framework to Detect and Prevent “Fake Video”
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Extending the Scope of Computational Archival Science: A Case Study on Leveraging Archival and Engineering Approaches to Develop a Framework to Detect and Prevent “Fake Video”

机译：扩展计算档案科学范围：利用档案和工程方法开发框架来检测和防止“假录像”的案例研究

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摘要

Thousands of videos are posted online every day. The affordability of video editing tools and social networks has facilitated the creation and spread of videos carrying disinformation, i.e. fake videos. Previous attempts to categorize disinformation have focused on content analysis and ascertaining the intention of creators. To extend these approaches, it is beneficial to incorporate the perspective of other fields that study the trustworthiness of records, such as archival science, to help detect and categorize fake videos. This paper proposes to leverage archival science in combination with computer engineering to devise a new framework for detecting and categorizing fake videos. In doing so, the paper offers a case study of the way in which Computational Archival Science, which blends archival and computational thinking, can be used to contribute to a novel approach towards solving the problem of fake videos.
机译：成千上万的视频每天都在线发布。视频编辑工具和社交网络的负担能力促进了携带虚假信息的视频的创建和传播，即假视频。以前的尝试分类虚拟信息已经侧重于内容分析和确定创作者的意图。为了延长这些方法，将其他领域的角度纳入这些方法，这些领域研究了研究记录的可信度，例如档案科学，以帮助检测和分类假视频。本文建议利用档案科学与计算机工程结合使用，设计用于检测和分类假视频的新框架。此外，该论文提供了对档案档案科学的案例研究，其中融合了档案和计算思维，可用于为解决假视频问题的新方法做出贡献。

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