Graph classification is a rapidly evolving discipline that applies sophisticated methods to assign categorical labels to complex network structures. This field bridges graph theory, machine learning ...

A research team has developed a new technology that enables to process a large-scale graph algorithm without storing the graph in the main memory or on disks. A KAIST research team has developed a new ...

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 ...

Experts from Factor joined KMWorld for a webinar, The Power of Context: Using AI and Knowledge Graphs to Enhance KM, to discuss semantics, knowledge graphs, ontologies, and more ...

Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...