Generally, items with missing modalities are dropped in multimodal recommendation.
However, with this work, we question this procedure, highlighting that it would further …

Human exposure to reality is multi-modal, and the brain processes it through multi-sensory
stimulation. As such, using multi-source intelligence can potentially improve results …

Multimodal learning has emerged as a powerful technique that leverages diverse data
sources to enhance learning and decision‐making processes. Adapting this approach to …

In domains such as fashion, music, food, and micro-video recommendation, items'
representation can be suitably enhanced through multimodal side information (extracted …

Multimodal-aware recommender systems (MRSs) exploit multimodal content (eg, product
images or descriptions) as items' side information to improve recommendation accuracy …

Multimodal recommender systems work by augmenting the representation of the products in
the catalogue through multimodal features extracted from images, textual descriptions, or …

In specific domains like fashion, music, and movie recommendation, the multi-faceted
features characterizing products and services may influence each customer on online …

Multi-modal learning has emerged as a powerful technique that leverages diverse data
sources to enhance learning and decision-making processes. Adapting this approach to …

Recommender systems (RSs) provide customers with a personalized navigation experience
within the vast catalogs of products and services offered on popular online platforms …

Abstract n the era of digital information overload on the Internet, recommender systems act
as filtering algorithms to provide users with items that might meet their interests according to …