Knowledge Graph Maintenance
Knowledge Graph Conference 2020
•
19m
Knowledge graphs are increasingly built using complex multifaceted machine learning based systems relying on a wide of different data sources. To be effective these must constantly evolve and thus be maintained. I present work on combining knowledge graph construction (e.g. information extraction) and refinement (e.g. link prediction) in end to end systems. I then discuss the challenges of ongoing system maintenance, knowledge graph quality and traceability.
Up Next in Knowledge Graph Conference 2020
-
Modeling Real Estate Ecosystem with C...
Cherre’s knowledge graph is a model of the entire US real estate ecosystem. The graph incorporates hundreds of millions of entities such as properties, addresses, individual and commercial owners, lenders, brokers, estate managers, lawyers etc. as nodes – while the edges are various types of conn...
-
Tutorial Rapid Knowledge Graph Develo...
The enterprise knowledge graphs help modern organizations to preserve the semantic context of abundant accessible information. They become the backbone of enterprise knowledge management and AI technologies with the ability to differentiate things versus strings. Still, beyond the hype of repacka...
-
Q&A | Francois Scharffe, Neda Abolhas...
Q&A of the first session of day 1. Here our own Francois Scharffe, Neda Abolhassani from Accenture Labs, Paul Groth from the University of Amsterdam and Ron Bekkerman from Cherre answer some questions from the audience.