Realtime Data Mining

Self-Learning Techniques for Recommendation Engines

Authors:

ISBN: 978-3-319-01320-6 (Print) 978-3-319-01321-3 (Online)

Table of contents (14 chapters)

  1. Front Matter

    Pages i-xxiii

  2. No Access

    Chapter

    Pages 1-9

    Brave New Realtime World: Introduction

  3. No Access

    Chapter

    Pages 11-14

    Strange Recommendations? On the Weaknesses of Current Recommendation Engines

  4. No Access

    Chapter

    Pages 15-40

    Changing Not Just Analyzing: Control Theory and Reinforcement Learning

  5. No Access

    Chapter

    Pages 41-56

    Recommendations as a Game: Reinforcement Learning for Recommendation Engines

  6. No Access

    Chapter

    Pages 57-90

    How Engines Learn to Generate Recommendations: Adaptive Learning Algorithms

  7. No Access

    Chapter

    Pages 91-118

    Up the Down Staircase: Hierarchical Reinforcement Learning

  8. No Access

    Chapter

    Pages 119-142

    Breaking Dimensions: Adaptive Scoring with Sparse Grids

  9. No Access

    Chapter

    Pages 143-181

    Decomposition in Transition: Adaptive Matrix Factorization

  10. No Access

    Chapter

    Pages 183-207

    Decomposition in Transition II: Adaptive Tensor Factorization

  11. No Access

    Chapter

    Pages 209-225

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

  12. No Access

    Chapter

    Pages 227-234

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

  13. No Access

    Chapter

    Pages 235-300

    Building a Recommendation Engine: The XELOPES Library

  14. No Access

    Chapter

    Pages 301-304

    Last Words: Conclusion

  15. No Access

    Chapter

    Pages E1-E10

    ERRATUM

  16. Back Matter

    Pages 305-313