Graph technology has become a requirement for the modern enterprise. Companies in virtually every industry, from healthcare to energy to financial services, are applying the power of graph analytics ...

Probabilistic graphs and uncertain data analysis represent a rapidly evolving research domain that seeks to reconcile the inherent imprecision of real-world data with robust computational models. By ...

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 ...

Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in their data management.

A new open-source library by Nvidia could be the secret ingredient to advancing analytics and making graph databases faster. The key: parallel processing on Nvidia GPUs. Nvidia has long ago stopped ...

Computer scientists from Carnegie Mellon University have devised a framework for running large-scale computations for tasks such as social network or Web search analysis efficiently on a single ...

The analysis of cancer biology data involves extremely heterogeneous data sets, including information from RNA sequencing, genome-wide copy number, DNA methylation data reporting on epigenetic ...

When relationships between entities are more important than the entities themselves, you have a business problem made for graph analysis Graph analysis is not a new technology, but many analytics ...