Collaborative Filtering: Non-Personalized item-to-item similarity

Question

I\'m trying to compute item-to-item similarity along the lines of Amazon\'s \"Customers who viewed/purchased X have also viewed/purchased Y and Z\". All of the examples and

Answer 1

There's a good O'Reilly book on this topic. While the whitepaper might lay the logic out in pseudo-code like that, I don't think that approach would scale very well. The calculations are all probability calculations, so things like Bayes' Theorem get used to say, "Given Person A purchased X, what's the likelihood they purchased Z?" Straightforward looping over the data is working too hard. You have to go through it all for each person.