R Text Mining Term Adjacency Matrix

I have created a Document Term Matrix from my Corpus using the tm package.

dtm <- DocumentTermMatrix(myCorpus, control=list(wordLengths=c(4, 20),
       bounds = list(global = c(1,13))))

I then created a Term-Term Adjacency Matrix.

ttm_results <- t(as.matrix(dtm)) %*% as.matrix(dtm)

When I inspect a sample of my results

ttm_results[200:205, 200:205]

I notice it is a very large but sparse dataset.

How might I remove rows that are essentially zeros?

I consider essentially zero to include rows like 1,2 and 5 which do not have adjacent terms.

How about this

#rebuilding your matrix 
m <- diag(6)
m[3, 3] = 71
m[4, 5] = 1
m[5, 4] = 1

m
     [,1] [,2] [,3] [,4] [,5] [,6]
[1,]    1    0    0    0    0    0
[2,]    0    1    0    0    0    0 
[3,]    0    0   71    0    0    0
[4,]    0    0    0    1    1    0
[5,]    0    0    0    1    1    0
[6,]    0    0    0    0    0    1

#answer
m[!rowSums(m)==1, ]