Knowledge Graphs (KGs) have emerged as a compelling abstraction for organizing the world’s structured knowledge, and as a way to integrate information extracted from multiple
The graph neural networks are trending because of their applications in a variety of predictive analytics tasks. When it comes to modelling the data available
Have you ever received a call from your bank because they suspected fraudulent activity? Most banks can automatically identify when spending patterns or locations have
I’m at a graph conference. The general sense is that property graphs are much easier to get started with than Knowledge Graphs. I wanted to
TensorFlow is a very powerful and open source library for implementing and deploying large-scale machine learning models. This makes it perfect for research and production.
Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may
Fraud detection is all about connecting the dots. We are going to see how to use graph analysis to identify stolen credit cards and fake
Social network analysis (SNA) is the methodical analysis of social networks.  Social network analysis views social relationships in terms of network theory, consisting of nodes (representing individual actors within the network) and ties (which
If you are choosing a platform for a workload, you might consider a graph database if you would describe that workload with any of these
We live in a connected world. There are no isolated pieces of information, but rich, connected domains all around us. Only a database that embraces
Natural relationships between data contain a gold mine of insights for business users. Unfortunately, traditional databases have long stored data in ways that break these
The identification and monitoring of terrorist or criminal networks are imperatives to detect threats and defeat attacks. Let’s see how Linkurious and graph visualizations can help
