Mining valuable hidden knowledge from large-scale data relies on the support of reasoning
technology. Knowledge graphs, as a new type of knowledge representation, have gained …

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 …

Reasoning is essential for the development of large knowledge graphs, especially for
completion, which aims to infer new triples based on existing ones. Both rules and …

Digitalisation trends of Industry 4.0 and Internet of Things led to an unprecedented growth of
manufacturing data. This opens new horizons for data-driven methods, such as Machine …

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

Knowledge graph completion aims to predict missing relations between entities in a
knowledge graph. In this work, we propose a relational message passing method for …

Abstract Knowledge graph embeddings that generate vector space representations of
knowledge graph triples, have gained considerable popularity in past years. Several …

Knowledge graph (KG) reasoning is becoming increasingly popular in both academia and
industry. Conventional KG reasoning based on symbolic logic is deterministic, with …

In recent years, reasoning over knowledge graphs (KGs) has been widely adapted to
empower retrieval systems, recommender systems, and question answering systems …