CurriculumDisentangledRecommendationwith NoisyMulti-feedback

They include three items that are sampled from the top popular (top 3000 for Amazon datasets and top 1/2 for MovieLens-1M) items at that time and one item randomly sampled from all the items. The whole dataset is chronologically divided to the train, valid, and test dataset by the ratio of 8:1:1. Note that our training and testing phase follow the sequential recommendation setting. For example, if one user's historical behavior is a sequence {1,2,3,,18,19,20}.