In hybrid recommendation, we start by creating a similarity matrix of items using content-based recommendation. This can be done by using the co-occurrence matrix or by using any distance measure to quantify the similarities between items. 

Let's assume that we currently have five items. Using content-based recommendations, we generate a matrix that captures the similarities between items and looks like this:

Let's see how we can combine this similarity matrix with a preference matrix to generate recommendations.