EliMRec: Eliminating Single-modal Bias in Multimedia Recommendation

Abstract

The main idea of multimedia recommendation is to introduce the profile content of multimedia documents as an auxiliary, so as to endow recommenders with generalization ability and gain better performance. However, recent studies using non-uniform datasets roughly fuse single-modal features into multi-modal features and adopt the strategy of directly maximizing the likelihood of user preference scores, leading to the single-modal bias. Owing to the defect in architecture, there is still room for improvement for recent multimedia recommendation.