Hi.

I've done some hierarchical clustering on a graph using cosine similarity on 
nodes:

library(lsa)
# get adj matrix
A = get.adjacency(g, sparse=FALSE)
# cosine similarity
S = cosine(A)
# distance matrix
D = 1-S
# distance object
d = as.dist(D)
# average-linkage clustering method
cc = hclust(d, method = "average")

I would like to convert the hclust object to a community object corresponding 
to the community structure with maximum modularity among the different cuts of 
the dendrogram. Is there a way to do this?

Thanks.

Massimo Franceschet
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