Knowledge Base


convert RDF-XML to ntriples
RDF adds the ability to give each link a kind of tag or category (also in the form of a URL) to further specify the meaning or kind of relationship of the link. (In fact in the first versions of HTML, link elements contain a "rel" attribute already hinting at how semantic links might be written.)

In a nutshell, the components of a triple can be one of three possible things:

  • A URI (or URL), shown between less-than/greater-than symbols, (i.e. <>)
  • A "literal" value displayed in quotation marks (e.g. "Michael Murtaugh"),
  • A "blank" node, (in the form _:blaHdiEBlah), which functions like a temporary URL, effectively allowing for grouping of triples without needing to actually come up with a URL.

rapper --output turtle

triples with the same subject appear as lists, subgrouped by predicate (type)

Every click on a facebook like button by a person generates a triple. this is the semantic web 3.0. video
Advertisement companies like boostable try to merge this across providers

An example: a 10-year-old female Taylor Swift fan and a 49-year-old male fan of Phil Collins both run a search for ‘best albums of 2012′.  Their world views and life experience are completely different, as is their understanding of what the ‘best’ music might be.  Should their search result be identical? On one hand, one might argue ‘yes, how else will people discover new things and broaden their horizons?’  One the other hand, is there really any value to telling the 49 year-old that Rihanna’s latest album made the top 50? And vice versa for the 10 year old and Rick Ross’s new EP? In reality, both of these people were actually trying to make a playlist for a roadtrip – but the search engine couldn’t know that because they didn’t choose to type it. But with access to what they’re saying to friends, imagine: instead of Google’s ‘did you mean’ function correcting spelling, it actually corrected meaning? ie. Did you mean you’re looking for great roadtrip music for your drive this weekend? link

tagging fails to capture the context, but in social context, chris is not just a string its a link to some specific person called chris
topic modeling given freebase entity tags (semantic topic modeling not just bag of words) [obsolete wordnet meaning] [topic modeling on wikipedia this ignore entities being discussed in each page actually have meaning] maybe combine some form of graph clustering and topic modeling.

streaming semantics, billions of triples