The Knowledge graph, a multi-relational graph that represents rich factual information
among entities of diverse classifications, has gradually become one of the critical tools for …

In recent years, neural systems have demonstrated highly effective learning ability and
superior perception intelligence. However, they have been found to lack effective reasoning …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

Knowledge graph reasoning (KGR), aiming to deduce new facts from existing facts based on
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …

As the concept of Industries 5.0 develops, industrial metaverses are expected to operate in
parallel with the actual industrial processes to offer “Human-Centric” Safe, Secure …

In recent years, temporal knowledge graph (TKG) reasoning has received significant
attention. Most existing methods assume that all timestamps and corresponding graphs are …

Abstract Knowledge graph reasoning is the fundamental component to support machine
learning applications such as information extraction, information retrieval, and …

Knowledge graphs (KG) are essential background knowledge providers in many tasks.
When designing models for KG-related tasks, one of the key tasks is to devise the …

Abstract The incompleteness of Knowledge Graphs (KGs) is a crucial issue affecting the
quality of AI-based services. In the scholarly domain, KGs describing research publications …

Numerous studies have been conducted to investigate the properties of large-scale
temporal graphs. Despite the ubiquity of these graphs in real-world scenarios, it's usually …