The simplest way to compute W from W is to let W = W , which boils down to using a dense, complete graph G with the unmodified all-pairs similarity as its edge weights.
it has been observed that a sparse W not only save time needed for classification, but also results in better classification accuracy 1 than the full similarity matrix W (Zhu, 2008).