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Adapting Recommender Systems to the New Data Privacy Regulations

机译:将推荐系统适应新的数据隐私法规

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摘要

Recommender systems are key enablers to provide personalization and to make systems be adapted to users' needs. Both, users and content or commercial providers benefit from these techniques. While user profiling is required during the recommendation process, it can also introduce additional threats to the user's privacy. New regulations come into place to palliate the misuse of personal information from companies and public institutions. However, there are no clear rules defined for recommender systems. We find in the literature different proposals to privacy-preserving recommender system, but none of them tackle the compliance with the General Data Protection Regulation (GDPR). In this work we suggest a set of guidelines to assess and implement GDPR compliant recommender systems. Recommender providers shall follow our guidelines to make sure that their systems are not only privacy-preserving, but also GDPR compliant.
机译:推荐系统是提供个性化的关键支持者,并使系统适应用户需求。两者,用户和内容或商业提供商都受益于这些技术。虽然在推荐过程中需要用户分析,但它也可以向用户的隐私介绍额外的威胁。新的法规到位,以滥用公司和公共机构的个人信息。但是,没有为推荐系统定义明确的规则。我们在文献中找到了不同的建议,以隐私保留的推荐系统,但它们都没有解决遵守常规数据保护规范(GDPR)。在这项工作中,我们建议一组准则来评估和实施GDPR标准的推荐系统。推荐提供商应遵循我们的指导方针,以确保其系统不仅保留了隐私保留,而且符合GDPR。

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