Graph database developer Neo4j Inc. is upping its machine learning game today with a new release of Neo4j for Graph Data Science framework that leverages deep learning and graph convolutional ...

Graph databases hold numerous attractions for financial services users, among them the ability to detect hidden patterns in data that could be harder to spot otherwise. Some financial institutions are ...

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

The paper elaborates on a technique for using knowledge graphs with machine learning; specifically, a branch of machine learning called reinforcement learning.

More information: Xiaorui Su et al, Interpretable identification of cancer genes across biological networks via transformer-powered graph representation learning, Nature Biomedical Engineering (2025).

This article explores what knowledge graphs are, why they are becoming a favourable data storage format, and discusses their potential to improve artificial intelligence and machine learning ...

Diffbot is a startup focused on using artificial intelligence to better provide companies information found on the internet. The core product is a knowledge graph they claim has mapped “over 10 ...

Rapid data collection is creating a tsunami of information inside organizations, leaving data managers searching for the right tools to uncover insights. Knowledge graphs have emerged as a solution ...

Today, TigerGraph rolled out several new features so cloud users can deliver more analytics and artificial intelligence (AI) power without leaving the confines of its database.