40 Algorithms Every Programmer Should Know

Generating recommendations

To make recommendations, we can multiply the matrices. Users are more likely to be interested in an item that co-occurs frequently with an item that they gave a high rating to:

Matrix[S] x Matrix[U] = Matrix[R]

This calculation is shown graphically in the following diagram:

A separate resultant matrix is generated for each of the users. The numbers in the recommendation matrix, Matrix[R], quantify the predicted interest of a user in each of the items. For example, in the resultant matrix the fourth item has the highest number, 58. So this item is highly recommended for this particular user.

Now, let's look into the ...