1 INTRODUCTION

2 PROBLEM DEFINITION  
2.1 Related Problems

3 LEARNING GUARANTEES  
3.1 Semi-supervised learning in offline scenarios  
3.2 Semi-supervised learning in online scenarios

4 METHODS  
4.1 Intrinsically SSL  
4.2 Self-training  
4.3 Learning by disagreement  
4.4 Representation Learning  
4.5 Unsupervised and SSL Drift Detection

5 FAIR COMPARATIVE ANALYSIS  
5.1 Evaluation of machine learning methods  
5.2 Evaluation of stream mining models  
5.3 Comparison of semi-supervised vs. supervised methods  
5.4 Reference data streams  
5.5 Unified fair evaluation

6 CONCLUSION AND PERSPECTIVES