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 ...

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking and ...

Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

Graph models have emerged as a pivotal framework in the analysis of strategic conflicts and the development of decision support systems. These models represent conflicts as networks, where nodes ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

If you are interested in learning how to build knowledge graphs using artificial intelligence and specifically large language models (LLM). Johannes Jolkkonen has created a fantastic tutorial that ...

In the age when data is everything to a business, managers and analysts alike are looking to emerging forms of databases to paint a clear picture of how data is delivering to their businesses. The ...

How would you feel if you saw demand for your favorite topic — which also happens to be your line of business — grow 1,000% in just two years’ time? Vindicated, overjoyed, and a bit overstretched in ...

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...