With the explosive growth of artificial intelligence (AI) and big data, it has become vitally
important to organize and represent the enormous volume of knowledge appropriately. As …

Human knowledge provides a formal understanding of the world. Knowledge graphs that
represent structural relations between entities have become an increasingly popular …

Communication systems to date primarily aim at reliably communicating bit sequences.
Such an approach provides efficient engineering designs that are agnostic to the meanings …

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 …

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 …

Incorporating knowledge graph (KG) into recommender system is promising in improving the
recommendation accuracy and explainability. However, existing methods largely assume …

Knowledge graphs (KGs) have been widely used in the field of artificial intelligence, such as
in information retrieval, natural language processing, recommendation systems, etc …

Knowledge graph (KG) embedding is to embed components of a KG including entities and
relations into continuous vector spaces, so as to simplify the manipulation while preserving …

A knowledge graph (KG), also known as a knowledge base, is a particular kind of network
structure in which the node indicates entity and the edge represent relation. However, with …

Commonsense reasoning is a long-standing challenge for deep learning. For example, it is
difficult to use neural networks to tackle the Winograd Schema dataset (Levesque et al …