1. Introduction  
2. Dynamic Network Models  
2.1. Discrete Model  
3. Taxonomy of Embedding Techniques  
3.1. Structural-first Model  
3.2. Temporal-first Model  
3.3. Others  
4. Discussion  
- Long-term Features Preservation  
- Out-of-sample Node Embedding  
- Prediction for Future Embedding  
5. Data Sets, Evaluation and Applications  
5.1. Datasets  
5.2. Practical Applications  
- Anomaly Detection  
- Recommender System  
- Traffic Forecasting  
5.3. Open Source Software  
6. Conclusion and Future Direction