Multi-modal Algorithms as a Promising Approach to Improving Recommendation Accuracy by Leveraging Additional Sources of Information

This paper explores the effect of multi-modal algorithms in recommendation systems. The objective is to identify and analyze methods employed recent research improve accuracy by leveraging additional sources information. findings suggest that are a promising approach improving accuracy, particularly when combining explicit implicit feedback, incorporating context awareness, multiple types data sources. novelty this lies its ability incorporate different modalities information, such as text, images, user behavior, enhance system various techniques context-aware user-item embedding, cross-modality utilization, multimodal embedding fusion-based recommendation. review provides valuable insights into effectiveness can guide future area.