How We Derive Context from Big Data

blog.urx.com

25 pointsjisaacso4 comments

Well done for the engineering feat here. Parsing Wikipedia at scale isn't easy.

Very surprised that they don't mention DBpedia though (http://wiki.dbpedia.org/) or discuss how they navigate through some big NLP challenges with Wikipedia, namely that many edits are made by bots.

DBpedia is a great, structured representation of Wikipedia. Agreed, there are many challenges, NLP being one. I think you'll like our other blog posts http://blog.urx.com/urx-blog/2015/7/28/named-entity-recognit...

Calculating context on mobile is a huge win for content providers, who can use the context to create deep links into other apps.

Example: I'm reading an article about James Bond, and ideally the phone can calculate that there's a new Bond movie, and I'm near a theater, and I'm free on Thursday night, and then create a link to buy tickets.

Great example! This is the exact problem URX is solving: empowering content providers to present their products within meaningful contexts.

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