In recent years, the rapid growth of online multimedia services, such as e-commerce
platforms, has necessitated the development of personalised recommendation approaches …

This paper studies the multi-modal recommendation problem, where the item multi-modality
information (eg, images and textual descriptions) is exploited to improve the …

Multimodal recommendation exploits the rich multimodal information associated with users
or items to enhance the representation learning for better performance. In these methods …

Many multimodal recommender systems have been proposed to exploit the rich side
information associated with users or items (eg, user reviews and item images) for learning …

In this paper, we present a novel multimodal framework for video recommendation based on
deep learning. Unlike most common solutions, we formulate video recommendations by …

Multimodal learning has shown promising performance in content-based recommendation
due to the auxiliary user and item information of multiple modalities such as text and images …

In multimodal-aware recommendation, the extraction of meaningful multimodal features is at
the basis of high-quality recommendations. Generally, each recommendation framework …

Multimodal recommender systems utilizing multimodal features (eg, images and textual
descriptions) typically show better recommendation accuracy than general recommendation …

Beyond conventional recommendation systems that rely merely on user-item interaction
data, multimodal recommendation systems additionally exploit the item multimodal data for …

With the increasing multimedia information, multimodal recommendation has received
extensive attention. It utilizes multimodal information to alleviate the data sparsity problem in …