Semantic Factor enhanced Alignment and Uniformity

Beyond Instance-Level Alignment and Uniformity: Semantic Factor Learning for Collaborative Filtering

Announce Type: new Abstract: Collaborative filtering (CF) is widely used in recommender systems (RecSys) due to its simplicity and efficiency. However, existing CF methods follow an instance-level learning paradigm. During the instance learning stage, a large number of uninteracted user-item instances, of which items are potential interested by the user, are incorrectly treated as true negative samples resulting in a severe limitation to the generalization and scalability of models.