You are correct, since centeredSumX2 equals zero, the Pearson similarity will be undefined (because of division by zero in the Pearson formula).
If you do not center the data that will be cosine similarity which is another common similarity metric used in recommender systems and it will not be undefined when a user has the same ratings for all items. On Tue, Apr 9, 2013 at 6:19 PM, yamo93 <yam...@gmail.com> wrote: > Hi, > > I use a user based recommender. > I've just discovered a strange behaviour of Pearson when a user has the same > ratings for all rated items. The system don't recommend anything in this > case for this user. > > I try an explanation : it is due to centered data (centeredSumX2 equals 0 in > this case). Is it exact ? > > Using UncenteredCosine as a workaround is it a good idea ? > > Thanks, > Yann.
