4 papers
PEARL: Path-Entity Aligned Relational Learning with Contextual Subgraphs for Inductive Knowledge Graph Completion
Yunchi Yang, Longlong Li, Cunquan Qu
Inductive knowledge graph completion (IKGC) aims to predict missing links involving entities unseen during training, requiring models to learn transferable relational and structura…
Cheeger--Hodge Contrastive Learning for Structurally Robust Graph Representation Learning
Mengyang Zhao, Longlong Li, Cunquan Qu
Graph Contrastive Learning (GCL) has emerged as a prominent framework for unsupervised graph representation learning. However, relying on augmentation design alone to define the in…
MISApp: Multi-Hop Intent-Aware Session Graph Learning for Next App Prediction
Yunchi Yang, Longlong Li, Jianliang Wu +1
Predicting the next mobile app a user will launch is essential for proactive mobile services. Yet accurate prediction remains challenging in real-world settings, where user intent…
MGKAN: Predicting Asymmetric Drug-Drug Interactions via a Multimodal Graph Kolmogorov-Arnold Network
Kunyi Fan, Mengjie Chen, Longlong Li +1
Predicting drug-drug interactions (DDIs) is essential for safe pharmacological treatments. Previous graph neural network (GNN) models leverage molecular structures and interaction…