[jwp]

What he said! I'd like to add that a key to squeezing more out of NathanRice's post is the phrase "conjugate prior." Another totally natural thing would be to use a Gaussian prior & likelihood, then update the posterior as ratings arrive. This would take advantage of the ordinality of ratings as NR suggests. Bishop's Machine Learning book goes into this sort of stuff in more depth.