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Who needs the semantic web when we have machine learning to extract the information we want?


Yes, Google surprised us all and made the semantic web unnecessary, even though I doubt it would have come to pass anyway. Consider a paper in 1998 by Sergey Brin, Larry Page, and others, that showed them finding the titles of books and the names of their authors amid the sludge of the World Wide Web:

> We begin with a small seed set of (author, title) pairs [...]. Then we find all occurrences of those books on the Web [...]. From these occurrences we recognize patterns for the citations of books. Then we search the Web for these patterns and find new books. --- http://dis.unal.edu.co/~gjhernandezp/psc/lectures/MatchingMa...

Starting with a seed of just five author-title pairs, their formula found thousands more.


Extracting information is not the issue. Figuring out what it is is what the Semantic Web (or any good Ontology) helps solve.

For a ML to provide that insight - requires the ML to have access to a good Ontology.


We are trying to build a global knowledge graph from the web using AI at diffbot.com.




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