机译:在跨平台边缘环境中用于保护隐私的移动服务推荐的基于两阶段局部性敏感哈希的方法
School of Information Science and Engineering, Qufu Normal University,State Key Laboratory for Novel Software Technology, Nanjing University;
Department of Electrical and Computer Engineering, University of Auckland;
State Key Laboratory for Novel Software Technology, Nanjing University;
Key Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Commerce,Mobile E-Business Collaborative Innovation Center of Hunan Province, Hunan University of Commerce;
School of Computing & Information Technology (SCIT), University of Wollongong;
Swinburne Data Science Research Institute, Swinburne University of Technology;
Mobile service recommendation; Distributed edge platform; Collaborative filtering; Privacy-preservation; Locality-sensitive hashing; MinHash;
机译:一种基于局部敏感度哈希的基于多源数据的云服务推荐方法
机译:分布式云环境中基于SimHash的隐私保护和可扩展服务推荐
机译:在移动边缘计算环境中使用功能学习的服务推荐QoS预测
机译:基于地方敏感散列的隐私保留分布式服务推荐
机译:使用移动地理信息系统和服务的优质移动平台在具有备用移动设备的现场环境中收集数据
机译:云环境中隐私保护服务推荐失败的异常处理方法
机译:基于位置敏感的散列的保护隐私的分布式服务建议
机译:基于分布式核心局部敏感哈希的快速图像导航。