Dave Gardner has put together a post about some work he did with the Joind.in API (an event feedback site) to apply collective intelligence to the results of the PHP UK Conference.

The term "collective intelligence" refers to intelligence that emerges from the collaboration of a group. In this case, we can leverage the data within joind.in and make "intelligent" recommendations. This post looks at building a simple recommendation engine using the data from joind.in. You can download the entire source code here (gzipped) or view via PasteBin here and try it out for yourself.

His code connects to the Joind.in API and fetches the event's talk information and the comments for each. His "calculatePearson" function then takes in two users and the set of ratings to figure out how similar their preferences are. There's also a bit of code that approaches it from a different angle - providing recommendations for users based on their own comments.