Deep Learning Recommendation System
Master's thesis on an Adaptive Context-Aware and Stacked Attention Network Based Recommendation System. Published in IEEE TKDE.
Recommendation SystemsDeep LearningPyTorchAttention NetworksTKDE
Adaptive Context-Aware Recommendation System
This project represents my Master’s thesis research at National Cheng Kung University (NCKU).
Research Focus
The research proposes an Adaptive Context-Aware and Stacked Attention Network Based Recommendation System, designed to significantly improve the accuracy and relevance of recommendations by deeply understanding user context and item features.
Recognition
The findings and methodology from this research have been successfully published in IEEE TKDE (Transactions on Knowledge and Data Engineering), a top-tier international journal.
You can view the full implementation and thesis details in the linked GitHub repository.