We at Roistr have released a demonstration of what our semantic relevance engine can do. With nothing other than a Twitter ID, we can extract a person's tweets and work out which of Amazon's current best-sellers will most fit that person.
It works using a semantic relevance comparison between the tweets (as a single document) and each book's editorial review ("blurb"). The assumption is that more similar texts imply closer interests.
You can try it out at http://Roistr.com/social and try anyone's Twitter ID.
The next step is to make it work using public posts from Facebook, GooglePlus and blogs!