Privacy-preserving concepts for supporting recommendations in decentralized OSNs

MSM '13 Pub Date : 2013-05-01 DOI:10.1145/2463656.2463659
M. Heupel, S. Scerri, Mohamed Bourimi, D. Kesdogan
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引用次数: 5

Abstract

Recommender systems depend on the amount of available and processable information for a given purpose. Trends towards decentralized online social networks (OSNs), promising more user control by means of privacy preserving mechanisms, lead to new challenges for (social) recommender systems. Information, recommender algorithms rely on, is no longer available, (i.e. central user registries, friends of friends), thus shared data is reduced and centralized processing becomes difficult. In this paper we address such drawbacks based on identified needs in the decentralized OSN di.me and present concepts overcoming those for selected functionalities. Besides this, we tackle the support of privacy advisory, warning the user of risks when sharing data.
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支持分散式osn中建议的隐私保护概念
推荐系统依赖于给定目的的可用和可处理信息的数量。分散式在线社交网络(OSNs)的趋势,通过隐私保护机制承诺更多的用户控制,给(社交)推荐系统带来了新的挑战。推荐算法所依赖的信息不再可用(即中央用户注册表,朋友的朋友),因此共享数据减少,集中处理变得困难。在本文中,我们根据分散的OSN di中确定的需求来解决这些缺陷。我和现在的概念克服了那些选定的功能。除此之外,我们还解决了隐私咨询的支持,警告用户共享数据时的风险。
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