§5.1 大数定律 law of large numbers §5.2 中心极限定理

§1 大数定理 §2 中心极限定理

今天的大环境 移动应用——崭新的应用客户端 云计算——超级应用服务器平台 大数据——实时数据/信息处理 未来的趋势

12.1 推荐系统概述 12.2 推荐算法 – 协同过滤 12.3 协同过滤实践 – 电影推荐系统

§5.1大数定律的概念 §5.2切贝谢夫不等式 §5.3切贝谢夫定理 §5.4中心极限定理

《电子商务 E-business》参考资料（大数据）：知识产生方式和科技决策支撑的重大变革_面向大数据和开源信息的科技态势解析与决策服

1 Introduction 2 Learning to Hash Isotropic Hashing Supervised Hashing with Latent Factor Models Supervised Multimodal Hashing with SCM Multiple-Bit Quantization 3 Distributed Learning Coupled Group Lasso for Web-Scale CTR Prediction Distributed Power-Law Graph Computing 4 Stochastic Learning Distributed Stochastic ADMM

1 Introduction 2 Learning to Hash Isotropic Hashing Scalable Graph Hashing with Feature Transformation Supervised Hashing with Latent Factor Models Column Sampling based Discrete Supervised Hashing Deep Supervised Hashing with Pairwise Labels Supervised Multimodal Hashing with SCM Multiple-Bit Quantization 3 Distributed Learning Coupled Group Lasso for Web-Scale CTR Prediction Distributed Power-Law Graph Computing 4 Stochastic Learning Fast Asynchronous Parallel Stochastic Gradient Descent Distributed Stochastic ADMM for Matrix Factorization 5 Conclusion

《电子商务 E-business》参考资料（大数据）：架构大数据_挑战_现状与展望

《电子商务 E-business》参考资料（大数据）：大数据带来大商业价值