As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

High sparse Knowledge Graph is a key challenge to solve the Knowledge Graph Completion task. Due to the sparsity of the KGs, there are not enough first-order neighbors to learn the features of ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

A knowledge graph, is a graph that depicts the relationship between real-world entities, such as objects, events, situations, and concepts. This information is typically stored in a graph database and ...

When we ask Siri, Alexa or Google Home a question, we often get alarmingly relevant answers. Why? And more importantly, why don’t we get the same quality of answers and smooth experience in our ...