问题
Assume that we have this data:
a <- c("ham","bamm","comb")
for 1-gram, this is the matrix representation of the above list.
# h a m b c o
# 1 1 1 0 0 0
# 0 1 2 1 0 0
# 0 0 1 1 1 1
I know that table(strsplit(a,split = "")[i]) for i in 1:length(a)
will give the separated count for each of them. But I don't know how use rbind
to make them as a whole since the lengths and column names are different.
After that, I want to use either Euclidean or Manhattan distance to find the similarity matrix for each of them as:
# ham bamm comb
# ham 0 3 5
# bamm 3 0 4
# comb 5 4 0
回答1:
You could also use the stringdist
package.
library(stringdist)
a <- c("ham","bamm","comb")
# stringdistmatrix with qgram calculations
stringdistmatrix(a, a, method = 'qgram')
[,1] [,2] [,3]
[1,] 0 3 5
[2,] 3 0 4
[3,] 5 4 0
recreating the 1-gram with stringdist
# creates the total count of the 1-gram
qgrams(a, q = 1L)
h m o a b c
V1 1 4 1 2 2 1
# create a named vector if you want a nice table
names(a) <- a
qgrams(a, .list = a, q = 1L)
#V1 is the total line
h m o a b c
V1 1 4 1 2 2 1
ham 1 1 0 1 0 0
bamm 0 2 0 1 1 0
comb 0 1 1 0 1 1
回答2:
You can do in this way :
s <- stack(setNames(strsplit(a,split=""),a))
m <- t(table(s))
> m
values
ind a b c h m o
ham 1 0 0 1 1 0
bamm 1 1 0 0 2 0
comb 0 1 1 0 1 1
Then using dist :
> as.matrix(dist(m,method='manhattan'))
ham bamm comb
ham 0 3 5
bamm 3 0 4
comb 5 4 0
来源:https://stackoverflow.com/questions/49252396/ngram-representation-and-distance-matrix-in-r