Hi, I`m making an online engine for item-to-item recommending movies. I have made some researches and I think that the best way to implement that is using pearson correlation and make a table with item1, item2 and correlation fields, but the problem is that after each rate of item I have to regenerate the correlation for in the worst case N records (where N is the number of items).
Another think that I read is the following article, but I haven`t thought a way to implement it.
So what is your suggestion to optimize this process? Or any other suggestions? Thanks.