Recently there's been quite an uptick in the use of
knowledge graphs in industry. I've been collaborating with
Ellie Young on the
KGC Newsletter to help spotlight use cases and the people involved in knowledge graph work:
https://www.knowledgegraph.tech/get-newsletters/There are two conference series collaborating on this project (KGC in New York City and Connected Data London in UK) which are some of the first to take an "industry-first" perspective on knowledge graphs, ontology, etc.
Here's a sampler from a few recent areas of focus:
I believe that knowledge graph work helps provide the "context" that tends to get removed from ML apps -- which are intended to generalize from data. We're seeing a flurry of deployments in enterprise: healthcare, finance, pharma, manufacturing, patent portfolio, inventory control, etc. As I mentioned in a recent post, according to the
NLP Industry Survey 2020, knowledge graph work is in the top four use cases for NLP in industry: the two technologies are highly complementary in the long run, and with a rise in use of
embedding and
inference use cases, KGs are making much use of deep learning.
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Paco Nathan
https://derwen.ai/paco------------------------------
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