As the name implies, this method computes the prediction on an item
*i* for a user *u* by computing the sum of the ratings given by the
user on the items similar to *i*. Each ratings is weighted by the
corresponding similarity *s*_{i,j} between items *i* and
*j*. Formally, using the notion shown in Figure 3 we can denote
the prediction *P*_{u,i} as

Basically, this approach tries to capture how the active user rates
the similar items. The weighted sum is scaled by the sum of the
similarity terms to make sure the prediction is within the predefined
range.