What visualization technique to best describe a recommendation dataset? I've written a simple recommender which generates recommendations for users based on what they have clicked. The recommender generates a data file with the following format:

userid,userid,simmilarity (between 0 and 1 - closer to 0 the more similar the users)
a,b,.2
a,c,.3
a,d,.4
a,e,.1
e,b,.3
e,c,.5
e,d,.8


I've looked at some graphs, but I'm not sure which one to use, or if are there other ones that will better display the user similarities from the dataset above. Any suggestions?

I'm aiming this visualization at business users who are not at all technical. I would just like to show them an easy to understand visual that details how similar some users are and so convince the business that for these users the recommendation system is useful.

@Steve Kallestad do you mean something like this :
I think you're looking for a similarity matrix (see bottom of the page). If you don't have data on similarity between certain pairs, you can always leave them as grey or white. Also, this will only work for data sets small enough to actually make out what's going on. I'd say 25 rows / columns maximum.

In a similarity matrix, x, and y coordinates correspond to the two things you're comparing, while a colormap magnitude represents similarity 

EDIT:
One thing you could do to replace the colormap is the insert, say, circles of different sizes according to the similarity metric. Or you could insert the numbers themselves, again, varying the size of the number as the magnitude of that number varies. Size usually works best is business visualizations.