On Sat, Mar 7, 2015 at 3:05 AM, Tevfik Aytekin <tevfik.ayte...@gmail.com> wrote:
> There can be two solutions: > 1. There should be a parameter n, which determines the minimum number > of common ratings needed to compute a similarity otherwise the system > should return NaN. > 2. The similarity should be computed using all the ratings, for the > above two vectors, the cosine similarity should be > > (3*5+2*4)/(sqrt(3^2+4^2+2^2)+sqrt(3^2+5^2+2^2+4^2)) > or 3. Use the more modern and scalable recommendation methods.
