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《工程(英文)》 >> 2018年 第4卷 第1期 doi: 10.1016/j.eng.2018.02.005

实现隐私保护个性化推荐服务

a Department of Computer Science, City University of Hong Kong, Hong Kong, China
b City University of Hong Kong, Shenzhen Research Institute, Shenzhen, Guangdong 518057, China
c Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China
d Institute of Cyber Security Research, Zhejiang University, Hangzhou, Zhejiang 310058, China

收稿日期: 2017-06-21 修回日期: 2017-09-26 录用日期: 2018-02-12 发布日期: 2018-02-16

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摘要

推荐系统对于向用户提供个性化服务至关重要。通过个性化的推荐服务,用户可以享受各种有针对性的推荐,如电影、书籍、广告、餐馆等。此外,个性化推荐服务极大地推动了在线业务收入的增长。尽管存在诸多好处,但采用个性化推荐服务通常需要收集用户的个人数据以进行处理和分析,会让用户怀疑个人隐私遭到严重侵犯。因此,在尊重用户隐私的前提下开发实用的隐私保护技术来维护个性化推荐服务提供的数据尤为重要。在本文中,我们提供了与隐私保护的个性化推荐服务相关文献的综合调查。我们介绍了个性化推荐系统的总体架构、其中的隐私问题以及集中于隐私保护个性化推荐服务的现有研究。根据个性化推荐和隐私保护的核心支撑技术,我们对现有研究进行了分类,并对其优缺点进行了深入的讨论和对比,特别是针对隐私和推荐的准确性。与此同时,我们也确定了一些未来的研究方向。

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