Sequential recommendation (SRS) has become the technical foundation in many
applications recently, which aims to recommend the next item based on the user's historical …

Multi-Domain Recommendation (MDR) has gained significant attention in recent years,
which leverages data from multiple domains to enhance their performance concurrently …

Deep Recommender Systems (DRS) are increasingly dependent on a large number of
feature fields for more precise recommendations. Effective feature selection methods are …

To enhance the efficacy of multi-scenario services in industrial recommendation systems,
the emergence of multi-domain recommendation has become prominent, which entails …

Multi-scenario recommender systems (MSRSs) have been increasingly used in real-world
industrial platforms for their excellent advantages in mitigating data sparsity and reducing …

GPRec explicitly categorizes users into groups in a learnable manner and aligns them with
corresponding group embeddings. We design the dual group embedding space to offer a …

Data-driven techniques have greatly empowered recommender systems in different
scenarios. However, many mainstream algorithms rely on black-box models, making them …

Accurate prediction of drug-drug interaction (DDI) is crucial to achieving effective decision-
making in medical treatment for both doctors and patients. Recently, many deep learning …

Owing to the impressive general intelligence of large language models (LLMs), there has
been a growing trend to integrate them into recommender systems to gain a more profound …