Personalized Adaptive Meta Learning for Cold-start User Preference Prediction
Personalized Adaptive Meta Learning for Cold-start User Preference Prediction
A common challenge in personalized user preference prediction is the cold-start problem. Due to the lack of user-item interactions, directly learning from the new users' log data causes serious over-fitting problem. Recently, many existing studies regard the cold-start personalized preference prediction as a few-shot learning problem, where each user is …