Multimodal recommender systems: A survey
The recommender system (RS) has been an integral toolkit of online services. They are
equipped with various deep learning techniques to model user preference based on …
equipped with various deep learning techniques to model user preference based on …
Fairness in recommender systems: research landscape and future directions
Recommender systems can strongly influence which information we see online, eg, on
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
Multimodal pretraining, adaptation, and generation for recommendation: A survey
Personalized recommendation serves as a ubiquitous channel for users to discover
information tailored to their interests. However, traditional recommendation models primarily …
information tailored to their interests. However, traditional recommendation models primarily …
A review of modern fashion recommender systems
The textile and apparel industries have grown tremendously over the past few years.
Customers no longer have to visit many stores, stand in long queues, or try on garments in …
Customers no longer have to visit many stores, stand in long queues, or try on garments in …
[HTML][HTML] Explaining recommender systems fairness and accuracy through the lens of data characteristics
The impact of data characteristics on the performance of classical recommender systems
has been recently investigated and produced fruitful results about the relationship they have …
has been recently investigated and produced fruitful results about the relationship they have …
Multi-view enhanced graph attention network for session-based music recommendation
Traditional music recommender systems are mainly based on users' interactions, which limit
their performance. Particularly, various kinds of content information, such as metadata and …
their performance. Particularly, various kinds of content information, such as metadata and …
Recommendation with generative models
Generative models are a class of AI models capable of creating new instances of data by
learning and sampling from their statistical distributions. In recent years, these models have …
learning and sampling from their statistical distributions. In recent years, these models have …
Exploiting negative preference in content-based music recommendation with contrastive learning
Advanced music recommendation systems are being introduced along with the
development of machine learning. However, it is essential to design a music …
development of machine learning. However, it is essential to design a music …
Predicting music relistening behavior using the ACT-R framework
Providing suitable recommendations is of vital importance to improve the user satisfaction of
music recommender systems. Here, users often listen to the same track repeatedly and …
music recommender systems. Here, users often listen to the same track repeatedly and …
Approximate homomorphic encryption based privacy-preserving machine learning: a survey
J Yuan, W Liu, J Shi, Q Li - Artificial Intelligence Review, 2025 - Springer
Abstract Machine Learning (ML) is rapidly advancing, enabling various applications that
improve people's work and daily lives. However, this technical progress brings privacy …
improve people's work and daily lives. However, this technical progress brings privacy …