Broad Learning Through Fusions

Applications in Machine Learning (1st Edition, 2019, Springer)

Jiawei Zhang and Philip S. Yu

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Highlights

  • background knowledge about machine learning and social networks
  • frontier development of network aligned problems and methods
  • start-of-art application problems studied across aligned networks
  • promising future development directions and suggestions
  • supplementary slides, toolkit, exercises and solution manual

Table of Contents

    Part I: Background Introduction
  • Chapter 1. Broad Learning Introduction
  • Chapter 2. Machine Learning Overview
  • Chapter 3. Social Network Overview
  • Part II: Information Fusion: Social Network Alignment
  • Chapter 4. Supervised Network Alignment
  • Chapter 5. Unsupervised Network Alignment
  • Chapter 6. Semi-supervised Network Alignment
  • Part III: Fusion Learning: Knowledge Discovery across Aligned Networks
  • Chapter 7. Link Prediction
  • Chapter 8. Community Detection
  • Chapter 9. Information Diffusion
  • Chapter 10. Viral Marketing
  • Chapter 11. Network Embedding
  • Part IV: Future Directions
  • Chapter 12. Frontier and Future Work Directions