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 ...

Part I of our series on graph analytics introduced us to graph analytics, and its brethren graph databases. We talked about the use of graph analytics to understand and visualize relationships between ...

The team proposed propose a novel entity-type-enriched cascaded neural network (E 2 CNN) that considers the overlap triple problem and entity-type information to construct a Chinese financial ...