Text clustering with Levenshtein distances

Question

I have a set (2k - 4k) of small strings (3-6 characters) and I want to cluster them. Since I use strings, previous answers on How does clustering (especially String clusteri

Answer 1

This may be a bit simplistic, but here's a code example that uses hierarchical clustering based on Levenshtein distance in R.

set.seed(1)
rstr <- function(n,k){   # vector of n random char(k) strings
  sapply(1:n,function(i){do.call(paste0,as.list(sample(letters,k,replace=T)))})
}

str<- c(paste0("aa",rstr(10,3)),paste0("bb",rstr(10,3)),paste0("cc",rstr(10,3)))
# Levenshtein Distance
d  <- adist(str)
rownames(d) <- str
hc <- hclust(as.dist(d))
plot(hc)
rect.hclust(hc,k=3)
df <- data.frame(str,cutree(hc,k=3))

In this example, we create a set of 30 random char(5) strings artificially in 3 groups (starting with "aa", "bb", and "cc"). We calculate the Levenshtein distance matrix using adist(...), and we run heirarchal clustering using hclust(...). Then we cut the dendrogram into three clusters with cutree(...) and append the cluster id's to the original strings.