If you mean metrics, the only one that I find really meaningful is a feedback loop to see what users are in fact interacting with, and we'll have something in place for that shortly. Synthetic metrics on recommendations quality don't really impress me because they ignore that recommendation algorithms are solving an human-computer interaction problem as much as they're solving a k-nearest-neighbors problem. I've got another article in the pipe on some of the interesting problems of ranking on real data, but it keeps getting pushed back since there's you know, a lot to do at the moment. :-)
If you mean examples, you can see our algorithm applied to link structure analysis on the related pages here:
http://pedia.directededge.com/
If you mean metrics, the only one that I find really meaningful is a feedback loop to see what users are in fact interacting with, and we'll have something in place for that shortly. Synthetic metrics on recommendations quality don't really impress me because they ignore that recommendation algorithms are solving an human-computer interaction problem as much as they're solving a k-nearest-neighbors problem. I've got another article in the pipe on some of the interesting problems of ranking on real data, but it keeps getting pushed back since there's you know, a lot to do at the moment. :-)