計算2個向量中每個單詞之間的Jaccard相似度

Question

我需要計算2個向量中每個單詞之間的Jaccard相似度。每個單詞由每個單詞組成。並提取最相似的單詞。

這裏是我不好不好慢代碼：

txt1 <- c('The quick brown fox jumps over the lazy dog') 
txt2 <- c('Te quick foks jump ovar lazzy dogg') 

words <- strsplit(as.character(txt1), " ") 
words.p <- strsplit(as.character(txt2), " ") 

r <- length(words[[1]]) 
c <- length(words.p[[1]]) 

m <- matrix(nrow=r, ncol=c) 
for (i in 1:r){ 
    for (j in 1:c){ 
    m[i,j] = stringdist(tolower(words.p[[1]][j]), tolower(words[[1]][i]), method='jaccard', q=2) 
    } 
} 

ind <- which(m == min(m))-nrow(m) 
words[[1]][ind] 

請幫我改善和美化大數據幀此代碼。

Answer 1

準備（添加tolower這裏）：

txt1 <- c('The quick brown fox jumps over the lazy dog') 
txt2 <- c('Te quick foks jump ovar lazzy dogg') 

words <- unlist(strsplit(tolower(as.character(txt1)), " ")) 
words.p <- unlist(strsplit(tolower(as.character(txt2)), " ")) 

獲取每個字的距離：

dists <- sapply(words, Map, f=stringdist, list(words.p), method="jaccard") 

對於每個單詞words從words.p找到最接近的詞：

matches <- words.p[sapply(dists, which.min)] 

cbind(words, matches) 
       matches 
[1,] "the" "te" 
[2,] "quick" "quick" 
[3,] "brown" "ovar" 
[4,] "fox" "foks" 
[5,] "jumps" "jump" 
[6,] "over" "ovar" 
[7,] "the" "te" 
[8,] "lazy" "lazzy" 
[9,] "dog" "dogg" 

編輯：

爲了讓你首先需要在words.p選擇從每個單詞words到所有字的最小距離的最佳匹配詞對：

mindists <- sapply(dists, min) 

這將讓每個字你最好的距離。然後你用最小距離選擇words字：

words[which.min(mindists)] 

或者在同一行：

words[which.min(sapply(dists, min))]