I'm trying to cluster similar documents using the R language. 
As a first step, I compute the term-document matrix for my set of documents.
Then I create the latent semantic space for the term-document matrix previously created. I decided to use use LSA in my expriment because the results of clustering using just the term-document matrix were awful .
Is possible to build a dissimilarity matrix (with cosine measure) using the the LSA space created? I need to do this because the clustering algorithm that I'm using requires a dissimilarity matrix as input.

Here is my code:

```
require(cluster);
require (lsa);

myMatrix = textmatrix("/home/user/DocmentsDirectory");
myLSAspace = lsa(myMatrix, dims=dimcalc_share());

```

I need to build a dissimilarity matrix (using cosine measure) from LSA space, so I can call the cluster algorithm as follows:

```
clusters = pam(dissimilartiyMatrix,10,diss=TRUE);

```

Any suggestions?

Thanks in advance!