Structure, Distance & Context
Incorporate structure, distance, and context from your graph into neural network training to unlock your data’s most powerful predictive attributes. Structure helps you build features based on important patterns in the graph. Distance introduces a quantifiable attribute useful in characterizing time, sequence, and flow features. Context supports a variety of nuanced features focused on the way your data elements relate to each other. Take the data you already have and maximize its value by developing neural network-based models with real-world awareness.