Precise: Privacy-aware recommender based on context information for cloud service environments
Precise: Privacy-aware recommender based on context information for cloud service environments
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DOI：
10.1109/mcom.2014.6871675
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发表时间：
2014-08
影响因子：
11.2
通讯作者：
Alberto Huertas Celdrán;M. Pérez;F. J. G. Clemente;G. Pérez
中科院分区：
文献类型：
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作者：
Alberto Huertas Celdrán;M. Pérez;F. J. G. Clemente;G. Pérez
基于位置的上下文感知系统为用户通过收集上下文信息获取定制服务开辟了新的可能性，特别是在用户的高移动性增加其可用性的系统中。在此背景下，本文提出了一个隐私保护的解决方案，提供上下文感知服务的基础上的位置在MCC。我们提出了一个中间件，称为PRECISE，它为用户提供自定义上下文感知的建议。这些建议是通过考虑上下文信息，用户的位置，隐私政策和以前访问过的地方。MCC在此解决方案中发挥了关键作用，将数据处理和存储需求转移到云端，以及弹性和负载平衡等进一步优势。在比较PRECISE与其他相关作品时进行了深入的讨论，证实了我们的解决方案改善了迄今为止最相关的建议。
Context-aware systems based on location open up new possibilities to users in terms of acquiring custom services by gathering context information, especially in systems where the high mobility of users increases their usability. In this context, this article presents a privacy-preserving solution offering context-aware services based on location in MCC. We propose a middleware, called PRECISE, which provides users with custom context-aware recommendations. These recommendations are given by considering the context information, and the users' locations, privacy policies, and previously visited places. MCC plays a key role in this solution, moving the data processing and storage needs to the cloud, as well as further advantages such as elasticity and load balancing. A thorough discussion when comparing PRECISE with other related works confirms that our solution improves the most relevant proposals so far.