图片共享的隐私设置建议

Jun Yu, Zhenzhong Kuang, Zhou Yu, D. Lin, Jianping Fan
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引用次数: 9

摘要

本文旨在同时考虑两个不可分割的隐私设置建议问题:(1)共享图像视觉内容的敏感性;(2)被授予用户的可信度。首先,开发了一种基于对象的图像内容敏感性(隐私)表示方法。其次,将社交网络上的用户聚类成一组具有代表性的社会群体,生成判别字典,用于用户可信度表征;最后,对树分类器进行分层训练,以推荐适合图像共享的隐私设置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Privacy Setting Recommendation for Image Sharing
This paper aims to simultaneously consider two inseparable issues for privacy setting recommendation: (1) sensitiveness of visual content of the images being shared; and (2) trustworthiness of users being granted. First, an object-based approach is developed for image content sensitiveness (privacy) representation. Secondly, the users on a social network are clustered into a set of representative social groups to generate a discriminative dictionary for user trustworthiness characterization. Finally, a tree classifier is trained hierarchically to recommend appropriate privacy settings for image sharing.
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