We take the opportunity to discuss the database market, graph, and beyond, with CEO and co-founder Claudius Weinberger and Head of Engineering and Machine Learning Jörg Schad. ArangoDB was ...

The relational database model was developed in the ... With industries increasingly adopting machine learning, it seems likely that knowledge graph technology will also evolve hand-in-hand.

The paper elaborates on a technique for using knowledge graphs with machine learning; specifically ... To apply the model on industry scale knowledge graphs would require special infrastructure." ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

Graph analytics platform TigerGraph has just released its new TigerGraph ML Workbench, a Jupyter-based Python development framework. TigerGraph says this machine learning toolkit “enables data ...

Using Knowledge Graphs for Ultimate Business Knowledge Data and key business information can continuously be extracted with the help of specialized AI techniques and machine learning models ... AI ...

It can deliver answers to graph ... the AI model using not just the raw tabular data, but also the interconnections that make up the network in the database. Performing machine learning (ML ...

Diagram representing the prediction pipeline from the ... Additional condition cuts date more recent than 1990. For the graph machine learning model, we group numerical features into range bins (the ...