As 2022 dawns, knowledge graphs bear the dubious distinction of being at the epicenter of AI and machine learning for two reasons. One is that, unassisted, they are one of the myriad manifestations of ...

Data flow graphs are directed acyclic graphs that describe a computation for TensorFlow. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional ...

In the first direction, I shall discuss how data management techniques can assist in generating user-friendly, configurable, queryable, and robust explanations for graph neural networks. In the second ...

That may not sound like a big deal in and of itself, but coupled with updates in machine learning and data science features, it points towards the future of graph databases.

Deeply connected graph data and machine learning provide the key to unlocking valuable insights for optimal decision-making in these areas. However, the adoption of graph-powered ML has historically ...

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 ...

Bringing knowledge graph and machine learning technology together can improve the accuracy of the outcomes and augment the potential of machine learning approaches. With knowledge graphs, AI language ...