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Tackle Problems that Cannot Be Solved with Traditional Machine Learning

A graph represents relationships between entities such as people, devices, locations, etc. Graph AI applies neural/convolutional network techniques on graphs to provide insights when the relationships between entities is as important as the entities’ attributes themselves.

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What is Graph AI?

Graph AI is the science of using Machine Learning on graphs to focus on the relationships between variables to achieve deeper insights. By using specific algorithms like clustering, partitioning, PageRank and shortest path, some problems become easier to solve. These include problems where centrality, connectivity, and path analysis play a key role in the analysis.

Advantages of Graph AI

Interpret many-to-many relationships in unstructured, fluctuating, variable datasets to enhance the accuracy of predictions

Enhance classification, pattern detection, and prediction accuracy when combined with AI-ML Graph Neural or Convolutional Networks (GNN/GCN)

Support visualizations to express large and complex interconnected data and help you discover relations between entities

How Lynx Analytics uses Graph AI ?