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Privacy policy inference of multiple user-uploaded images on social context websites (Automated generation of privacy policy)

机译:在社交上传网站上的多个用户上传的图像的隐私政策推断(自动生成隐私政策)

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Social networking websites are the most active websites on the Internet and millions of people use them every day to engage and connect with other people. Twitter, Facebook, LinkedIn and Google Plus seems to be the most popular Social networking websites on the Internet. In this manner, recommendation policy is required which supply client with an adaptable help for organizing security settings in much easier way. Images are shared extensively now days on social sharing sites. Sharing takes place between friends and acquaintances on a daily basis. In this thesis, we are implementing an Adaptive Privacy Policy Prediction (A3P) system which will provide users a disturbance free privacy settings experience by automatically generating personalized policies.
机译:社交网站是互联网上最活跃的网站,数百万人每天使用它们与其他人联系。 Twitter,Facebook,LinkedIn和Google Plus似乎是互联网上最受欢迎的社交网站。以这种方式,需要推荐策略,其中提供具有适应性帮助的客户端,以便以更容易的方式组织安全设置。现在在社交共享网站上广泛共享图像。每天在朋友和熟人之间分享。在本文中,我们正在实施自适应隐私策略预测(A3P)系统,该系统将通过自动生成个性化策略来提供用户干扰自由度设置体验。

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