n articles and a list of articles for each article implying similarity, e.g.,
a1 -> a3, a5 means
a5 are similar to
a1. Similarity here is 0 or 1 that is either two articles are similar or not; there is no floating point value.
Now, I want to cluster these articles into let's say
k clusters. I can't directly apply KMeans to it, since these articles are not in vector form. Also I could try Spectral Clustering, but I don't understand in what form output is returned by Spectral Clustering (or Power Iteration Clustering).