Result Dithering? Why randomly shuffle results?
This is not an answer but rather a comment. I would need 50 reputation to comment.

I think in its nature, a recommendation problem is a greedy algorithm to a search/optimization problem. However, the process is biased and local. The users see and react to what they can see, and the algorithm will only reinforce it. Dithering is a way to break up the bias and make the search more global.

What I have been doing is a bit different than dithering, but similar idea. Instead of ranking, I converted the matching score to log linear probability, and "sort" the item/person by probability. An example is, P(a)=0.2, P(b)=0.8, then b has 80% of chance on top, while a has 20% of chance on top.

Like to hear how others hear about it too.