As a powerful expression of human knowledge in a structural form, knowledge graph (KG)
has drawn great attention from both the academia and the industry and a large number of …

With the rapid advancement and deployment of intelligent agents and artificial general
intelligence (AGI), a fundamental challenge for future networks is enabling efficient …

Wikidata has been increasingly adopted by many communities for a wide variety of
applications, which demand high-quality knowledge to deliver successful results. In this …

The standard evaluation protocol for measuring the quality of Knowledge Graph Completion
methods-the task of inferring new links to be added to a graph-typically involves a step …

In spite of its wide usage in various applications, existing construction methods for
Knowledge Base (KB) are still on their way to obtaining 100% correct facts. Thus, employing …

While our running example in this book was node classification, and also the benchmark
datasets discussed above use mostly node classification as a target (with a few exceptions) …

Abstract Knowledge graphs are data storage structures that rely on principles from graph
theory to represent information. Specifically, facts are stored as triples which bring together …

Addressing these issues and leveraging advancements in natural language processing,
machine learning, and database technologies is crucial for developing more accurate …