With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an indispensable and important component in our daily lives, providing …

Social recommender systems (SocialRS) simultaneously leverage the user-to-item
interactions as well as the user-to-user social relations for the task of generating item …

With the explosive growth of online information, the significant application value of
recommender systems has received considerable attention. Since user–item interactions …

The advancement in internet technology has enabled the use of increasingly sophisticated
data by recommendation systems to enhance their effectiveness. This data is comprised of …

Filters are fundamental in extracting information from data. For time series and image data
that reside on Euclidean domains, filters are the crux of many signal processing and …

Graph Neural Network (GNN) based social recommendation models improve the prediction
accuracy of user preference by leveraging GNN in exploiting preference similarity contained …

Modeling users' short-term dynamic and long-term static interests to enhance Point-of-
Interests (POI) recommendation performance has shown lots of advantages. Since users' …

Industrial products typically lack defects in smart manufacturing systems, which leads to an
extremely imbalanced task of recognizing surface defects. With this imbalanced sample …

In the rapidly evolving field of machine learning (ML), data augmentation (DA) has emerged
as a pivotal technique for enhancing model performance by diversifying training examples …

Large language models (LLMs) have demonstrated remarkable capabilities and have been
extensively deployed across various domains, including recommender systems. Numerous …