Abstract Knowledge Graph (KG) provides high-quality structured knowledge for various
downstream knowledge-aware tasks (such as recommendation and intelligent question …

Graph convolutional networks (GCNs) have a strong ability to learn graph representation
and have achieved good performance in a range of applications, including social …

Abstract The goal of Knowledge Tracing (KT) is to estimate how well students have
mastered a concept based on their historical learning of related exercises. The benefit of …

Abstract “Knowledge tracing (KT)” is an emerging and popular research topic in the field of
online education that seeks to assess students' mastery of a concept based on their …

In real-world intelligent transportation systems, the spatiotemporal traffic data collected from
sensors often exhibit missing or corrupted data, significantly hindering the development of …

The outbreak of the novel coronavirus disease (COVID-19) has been ongoing for almost two
years and has had an unprecedented impact on the daily lives of people around the world …

Skeleton-based human action recognition has caused wide concern, as skeleton data can
robustly adapt to dynamic circumstances such as camera view changes and background …

Among existing knowledge graph based question answering (KGQA) methods, relation
supervision methods require labeled intermediate relations for stepwise reasoning. To avoid …

With recent advancements in graph neural networks (GNN), GNN-based recommender
systems (gRS) have achieved remarkable success in the past few years. Despite this …

Traffic forecasting constitutes a task of great importance in intelligent transport systems.
Owing to the non-Euclidean structure of traffic data, the complicated spatial correlations, and …