Hi, I've used LogLikelihood Similarity in user based nearest neighborhood collaborative filtering and it has given good results (better than the others).
I have read the blog post by Ted Dunning ( http://tdunning.blogspot.com.tr/2008/03/surprise-and-coincidence.html) also looked at the implementation in Mahout. However, I still do not understand "why" this similarity metric works. I'm trying to give it a probabilistic interpretation in order to understand the logic behind. Any probabilistic interpretation should define random variables, events, etc. However, my attempts in this respect have been unsuccessful. Any help will be appreciated. Thanks