Hypergraphs have attracted increasing attention in recent years thanks to their flexibility in
naturally modeling a broad range of systems where high-order relationships exist among …

Since group activities have become very common in daily life, there is an urgent demand for
generating recommendations for a group of users, referred to as group recommendation …

Multimodal sentiment analysis (MSA) aims to detect the sentiments from language (text),
audio, and visual (facial expressions) modalities. The main challenge in MSA is how to …

Identifying the potential associations among drugs, microbes, and diseases is of great
significance in exploring the pathogenesis and improving precision medicine. There are …

Recently, many E-commerce search models are based on Graph Neural Networks (GNNs).
Despite their promising performances, they are (1) lacking proper semantic representation of …

In the world of E-Commerce, the core task is to understand the personalized preference from
various kinds of heterogeneous information, such as textual reviews, item images and …

Abstract Hypergraph Neural Network (HyperGNN) is an emerging type of Graph Neural
Networks (GNNs) that can utilize hyperedges to model high-order relationships among …

Recently, increasing attention has been paid to mining clinical treatment patterns from
electronic medical records (EMRs), which provide physicians with explicit knowledge to …

In the real world, relationships between objects are often complex, involving multiple
variables and modes. Hypergraph neural networks possess the capability to capture and …

Recently, personalized product search attracts great attention and many models have been
proposed. To evaluate the effectiveness of these models, previous studies mainly utilize the …