Modeling Dynamic Missingness of Implicit Feedback for Sequential Recommendation

Implicit feedback is widely used in collaborative filtering methods for sequential recommendation. It is well known that implicit feedback contains a large number of values that are missing not at random (MNAR); and the missing data is a mixture of negative and unknown feedback, making it difficult to learn users’ negative preferences. Recent studies modeled exposure更多