Knowledge Graph Convolution Networks: Introducing Grakn Labs to Seattle | Online
About this event
As humans we use our knowledge, our reasoning and our understanding of situational context to make accurate predictions about the world around us; machine learning doesn’t typically make use of any of this rich information. Not to mention it is far too complex for today’s databases.
We need an expressive data model and an intelligent query language to perform knowledge engineering over complex datasets.
We present Knowledge Graph Convolutional Networks (KGCN): a method for performing machine learning over a Grakn Knowledge Graph, which captures micro-context and macro-context for any Concept within the graph.
There will be beers, pizza, code, and most certainly a good time!
Takeaways
- How KGCN allows for the capture of micro-context and macro-context for any Concept within a knowledge graph.
- Introduction to Knowledge Graphs within the context of Machine Learning
