Find threshold in large dataset I have a problem. I have a data set with some users and their ratings in several movies. The movies are separated into 19 genres. 

I want to cluster the users by their preferences(ratings in the movies). The problem is, that I want to find a $threshold ( θ )$ to do the clustering, but I do not know how to do this, because the data are discrete and I cannot use the statistics methods that I know.
The threshold is the maximum distance that two users can have to be in the same cluster, like 2 users that likes the same genre movies or have little differences in their tastes. 

I've tried to find a threshold using simple statistics. For example, for a user sum all of his ratings in a genre and divide the result via the number of ratings and find some means in some genres, but I didn't got an answer. 

Note: I must use BSAS
Somehow you have to come up with some sort of numerical classification system for your movie genres.
I would start by creating a relationship tree between genres.  For example action movies and then action movies with comedy and then action movies with comedy with animation etc.

You could develop a whole Forest of trees that relate movie genres to one another.  You can then test the genres paths of individuals to compare.