Influenced by the great success of deep learning in computer vision and language
understanding, research in recommendation has shifted to inventing new recommender …

With the growing volume of online information, recommender systems have been an
effective strategy to overcome information overload. The utility of recommender systems …

Recommender systems have become an essential tool to help resolve the information
overload problem in recent decades. Traditional recommender systems, however, suffer …

With the growth of online information, varying personalization drifts and volatile behaviors of
internet users, recommender systems are effective tools for information filtering to overcome …

Recommendation systems are considered as one of the important components of e-
commerce platforms due to their direct impact on profitability. In this study, we propose a …

Generative recommendation has emerged as a promising paradigm aimed at augmenting
recommender systems with recent advancements in generative artificial intelligence. This …

In a collaborative-filtering recommendation scenario, biases in the data will likely propagate
in the learned recommendations. In this paper we focus on the so-called mainstream bias …

Movie recommendation systems provide users with ranked lists of movies based on
individual's preferences and constraints. Two types of models are commonly used to …

Textual reviews contain fine-grained information that can effectively infer user preferences
over the items. Accordingly, the latest studies in the field of recommender systems exploit …

In recent years, fashion e-commerce has become more and more popular. Since there are
so many fashion products provided by e-commerce retailers, it is necessary to provide …