GitHub - jiwidi/MASTER_THESIS: Master thesis in collaboration with H&M

This thesis shows how NLP Deep Learning methods, trained on user interactions sequences at H&M website, can be used to model user behavior and create personalized recommendations. We performed multiple experiments to prove how an ordered user history helps the model learn. Both item and user representations proved themselves to play an important role in our model's performance. New models won at performance but also saw different patterns on recommended items, recommending less popular items, and more expensive than our baseline model. We believe it is the powerful representation learning and the ability to capture order within sequences that are responsible for the performance improvements.