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It’s cool, I’m getting pretty accurate tags for the companies I’ve searched. How does this work?


we start with some automated content acquisition, before we use nlp for keyword extraction and tagging. The company-tag description is then located in a huge tech-domain-specific vector space. From vector space similarities and a couple of heuristics, we derive the company classification.


Worked with Orient back in 2012, had some issues regarding performance and switched. Following the news about them, I thought they had made great progress. This benchmark kind of shows the exact opposite.


Really helpful description for things to watch masteriung a shift to graphs. It really is a challenge. The 'triviality gap' was a heads up, especially for veteran IT staff.


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