Sure, I'm implementing this today, just a simple version of what's been discussed. What would be call this? It's basically item-based recommendation.
On Fri, Dec 4, 2009 at 8:57 AM, Gökhan Çapan <[email protected]> wrote: > ith row of the matrix A'A contains all items and their similarity degrees to > the item that is represented at ith column of the matrix A. > I guess it is enough using only a subset of A'A at the final step, that is, > the rows which represent the items that are in active user's history. > btw, I also want to contribute to that implementation, if we can decide the > algorithm.
