In this article, we provide a comprehensive introduction to knowledge graphs, which have
recently garnered significant attention from both industry and academia in scenarios that …

Equipping machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

近年来, 随着互联网技术和应用模式的迅猛发展, 引发了互联网数据规模的爆炸式增长,
其中包含大量有价值的知识. 如何组织和表达这些知识, 并对其进行深入计算和分析备受关注 …

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 …

Abstract Rules over a Knowledge Graph (KG) capture interpretable patterns in data and
various methods for rule learning have been proposed. Since KGs are inherently …

Abstract Representation learning on a knowledge graph (KG) is to embed entities and
relations of a KG into low-dimensional continuous vector spaces. Early KG embedding …

近年来, 随着互联网技术和应用模式的迅猛发展, 引发了互联网数据规模的爆炸式增长,
其中包含大量有价值的知识. 如何组织和表达这些知识, 并对其进行深入计算和分析备受关注 …

Abstract Knowledge graphs (KGs) are huge collections of primarily encyclopedic facts. They
are widely used in entity recognition, structured search, question answering, and other …

Rule learning from large datasets has regained extensive interest as rules are useful for
developing explainable approaches to many applications in knowledge graphs. However …

Entity-centric knowledge bases are large collections of facts about entities of public interest,
such as countries, politicians, or movies. They find applications in search engines, chatbots …