• By Franz Inc.
  • 10 May, 2023

AI and Machine Learning Summit

Embracing the Power of Knowledge Graphs

Build Predictions With Machine Learning & Graph Neural Networks
Probably the most important reason for building knowledge graphs has been to answer this age-old question: “What is going to happen next?” Given the data, relationships, and timelines we know about a customer, patient, product, etc. (“the entity of interest”), how can we confidently predict the most likely next event? Graph neural networks (GNNs) have emerged as a mature AI approach for knowledge graph enrichment. GNNs enhance neural network methods by processing graph data through rounds of message passing. Aasman describes how to use graph embeddings and regular recurrent neural networks to predict events via GNNs and demonstrates creating a GNN in the context of a knowledge graph for building event predictions.

AI and Machine Learning Summit

Jans Aasman, CEO, Franz Inc.

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