使用机器学习技术的社交媒体网站内容过滤

U. Tambe, N.R. Kakad, S. Suryawanshi, S. S. Bhamre
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引用次数: 0

摘要

为了在人与人之间建立社交网络或社会关系,我们使用社交网络平台,如Facebook, Twitter,应用程序等。使用这种媒体,用户可以分享他们对特定事物的看法和意见。许多人出于个人兴趣、娱乐、炒股或商业目的使用他们的媒体。如今,用户安全是社交网站的主要关注点。在线社交网络在内容过滤方面提供了一点支持。在本文中,我们提出了一个系统,该系统为发布在社交网站上的恶意内容提供安全性。为了过滤可能是不需要的消息、标记图像或低俗图像的内容,我们提出了三层架构。用户也可以使用自动阻塞功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Content Filtering of Social Media Sites Using Machine Learning Techniques
To build a social network or social relations between people, we use social networking platforms like Facebook, Twitter, apps, etc. Using this media, users can share their views and opinions about a particular thing. Many people use their media for personal interests, entertainment, the market stocks, or business purposes. Nowadays, user security is the major concern for social networking sites. Online social networks give a little bit of support regarding content filtering. In this article, we proposed a system that provides security regarding malicious content that is posted on their social networking sites. To filter the content that might be unwanted messages, labeled images, or vulgar images, we proposed three level architecture. The user can use the auto-blocking facility as well.
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