This repository presents a study of ranking algorithms used in recommendation systems, together with the implementation and evaluation of the SASRec (Self-Attentive Sequential Recommendation) model.
The project combines a literature review of modern ranking techniques with a practical implementation of a deep learning–based sequential recommendation system.
- Study ranking algorithms in recommendation systems
- Explore modern recommendation techniques
- Implement the SASRec model
- Evaluate recommendation performance
- Analyze sequential recommendation methods
- Python
- PyTorch
- SASRec
- NumPy
- Pandas
- Matplotlib
- Ranking Algorithms
- Sequential Recommendation
- Self-Attention Mechanism
- Transformer-based Recommendation
- Top-K Recommendation
- Recommendation Evaluation Metrics
ranking-algorithm-in-recommendation-systems/
│
├── report/
│ └── RANKING_ALGORITHM_IN_RECOMMENDATION_SYSTEMS.pdf
│
└── SASRec/
The complete project report is available in the report folder.
If GitHub cannot preview the PDF, simply download it and open it locally.
Beyzanur Arslan
Recommendation Systems Project
2026
