CODEWITHSUNDEEP
rstringtext-miningstring-matchingtext-classification
Prateek Prabhat
Prateek Prabhat

Reputation: 31

Matching multiple words amongst strings and creating a matrix to depict the answer

I have got a file with 5 reviews. As follows :

text <- c("Orange is the new black", " I love smoking Marlboro black",
    "I love oranges before they go black", "My diary is black, so is my hair",
    "Is it okay to drink and smoke black")

Now what I want do is make a 5 X 5 matrix, which tells me which words are common between 2 different reviews.

The solution will look something like a table/ matrix with 5 column and 5 rows, having 25 elements. It's diagonal element will be 0.

Now, I have a basic idea of text mining. But how should i do this particular task.

This is just a test run, I actually have to make a matrix having 100 rows and 100 column.

Upvotes: 1

Views: 72

Answers (1)

CPak
CPak

Reputation: 13581

Maybe something like this

all_words <- stringr::str_extract_all(text, "\\w+")
I <- expand.grid(seq_along(text), seq_along(text))
L <- map2(I$Var1, I$Var2, ~paste(intersect(all_words[[.x]], all_words[[.y]]), collapse="|"))
mat <- matrix(L, nrow=5)
diag(mat) <- NA
mat

     # [,1]       [,2]           [,3]           [,4]       [,5]   
# [1,] NA         "black"        "black"        "is|black" "black"
# [2,] "black"    NA             "I|love|black" "black"    "black"
# [3,] "black"    "I|love|black" NA             "black"    "black"
# [4,] "is|black" "black"        "black"        NA         "black"
# [5,] "black"    "black"        "black"        "black"    NA

For counts of common words do

L <- map2(I$Var1, I$Var2, ~length(intersect(all_words[[.x]], all_words[[.y]])))
mat <- matrix(L, nrow=5)
diag(mat) <- NA
mat

     # [,1] [,2] [,3] [,4] [,5]
# [1,] NA   1    1    2    1   
# [2,] 1    NA   3    1    1   
# [3,] 1    3    NA   1    1   
# [4,] 2    1    1    NA   1   
# [5,] 1    1    1    1    NA

Upvotes: 1

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