Speakers: Alessandro Negro, Chief Scientist, GraphAware
Abstract: In recent years, knowledge graphs are gaining significant traction across industries. This kind of graph excels uniquely at providing in-depth contextual knowledge so needed by organizations to successfully differentiate and compete today- particularly when leveraging unstructured data using NLP/U and Machine Learning on the graph.
But where is the knowledge that is created from the combined sources? And how can we start surfacing new, high value insights that we could not obtain before?
An example of how this can work is Hume, a graph-powered insights engine. It uses an innovative approach, creating what we call a Collaborative Knowledge Graph (CKG). In the CKG, Hume connects, enriches, and transforms data from structured and especially unstructured sources in order to liberate knowledge, discover hidden insights, and unlock new opportunities difficult or impossible to detect before.
By ingesting and analyzing the details of your domain and the nuances of your most complex business challenges, and by enriching the CKG with external knowledge sources such as Wikidata, private knowledge bases and more, Hume shows one way to deliver on the value and potential of knowledge graphs.