avoid a loop

library(ecodist)
a <- c(1,1,1,2,2,3,3,3,3)
b <- c("a","b","c","a","d","a", "b", "e", "f")

x <- crosstab(a, b, rep(1, length(a)))
x

x %*% t(x)

Let's suppose I have userids and associated attributes... ?columns a and b

a <- c(1,1,1,2,2,3,3,3,3)
b <- c("a","b","c","a","d","a", "b", "e", "f")

so a unique list of a would be

id <- unique(a)

I want a matrix like this...

? ? [,1] [,2] [,3]
[1,] ? ?3 ? ?1 ? ?2
[2,] ? ?1 ? ?2 ? ?1
[3,] ? ?2 ? ?1 ? ?4

Where element i,j is the number of items in b that id[i] and id[j] share...

So for example, in element [1,3] of the result matrix, I want to see
2. ?That is, id's 1 and 3 share two common elements in b, namely "a"
and "b".

This is hard to articulate, so sorry for the terrible description
here. ?The way I have solved it is to do a double loop, looping over
every member of the id column and comparing it to every other member
of id to see how many elements of b they share. ?This takes forever.

Thanks

cn