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Wednesday, January 16, 2019

Ontologies vs Knowledge Graphs

Challenging thoughts, which we examined for some time in the enterprise.   Not solved there either, or what it would take to construct, use and maintain this from either direction.       Ultimately it's the most important idea we can implement well to solve real, but also changing business problems in context.

Where Ontologies End and Knowledge Graphs Begin

#ODSC - The Data Science Community

Ontologies have been present in artificial intelligence research for at least forty years, coming into their own in the ’80s on the back of a research wave that catapulted them into popularity by the mid-‘90s. However, interest in ontologies waned by the 2000s as machine learning became the hot new technology for search engines and advertising. But in the past decade, two words have pushed ontologies and semantic data back into the spotlight: knowledge graphs.

Knowledge graphs have been embraced by numerous tech giants, most notably Google, which is responsible for popularizing the term. But that new widespread attention from the research community has helped foment a significant debate among knowledge representation experts: what even is a knowledge graph?

In truth, no one is really sure — or at least there isn’t a consensus.  .... "

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