Realtime Data Mining

Chapter 1 Brave New Realtime World: Introduction

Chapter 2 Strange Recommendations? On the Weaknesses of Current Recommendation Engines

Chapter 3 Changing Not Just Analyzing: Control Theory and Reinforcement Learning

Chapter 5 How Engines Learn to Generate Recommendations: Adaptive Learning Algorithms

Chapter 6 Up the Down Staircase: Hierarchical Reinforcement Learning

Chapter 7 Breaking Dimensions: Adaptive Scoring with Sparse Grids

Chapter 8 Decomposition in Transition: Adaptive Matrix Factorization

Chapter 9 Decomposition in Transition II: Adaptive Tensor Factorization

Chapter 10 The Big Picture: Toward a Synthesis of RL and Adaptive Tensor Factorization

Chapter 11 What Cannot Be Measured Cannot Be Controlled: Gauging Success with A/B Tests

Chapter 12 Building a Recommendation Engine: The XELOPES Library

Chapter 13 Last Words: Conclusion

Chapter 14 ERRATUM