如何在 R 数据库中将相似的字符串分组在一起

我的小标题只有 1 列，称为“标题”。

> dat
# A tibble: 13 x 1
   title                                          
   <chr>                                          
 1 lymphoedema clinic                             
 2 zostavax shingles vaccine                      
 3 xray operator                                  
 4 workplace mental health wellbeing workshop     
 5 zostavax recall toolkit                        
 6 xray meetint                                   
 7 workplace mental health and wellbeing          
 8 lymphoedema early intervenstion                
 9 lymphoedema expo                               
10 lymphoedema for breast care nurses             
11 xray meeting and case studies                  
12 xray online examination                        
13 xray operator in service paediatric extremities

我希望找到类似的记录并将它们分组在一起（同时保留它们的索引）：

> dat
# A tibble: 13 x 1
   title                                          
   <chr>                                          
 1 lymphoedema clinic   
 8 lymphoedema early intervenstion                
 9 lymphoedema expo                               
10 lymphoedema for breast care nurses                             
 2 zostavax shingles vaccine 
 5 zostavax recall toolkit                                
 3 xray operator                                  
 6 xray meetint     
11 xray meeting and case studies                  
12 xray online examination                        
13 xray operator in service paediatric extremities
 4 workplace mental health wellbeing workshop                                  
 7 workplace mental health and wellbeing          

我使用下面的函数来查找彼此足够接近的字符串（cutoff = 0.75）

compareJW <- function(string1, string2, cutoff)
{
  require(RecordLinkage)
  jarowinkler(string1, string2) > cutoff
}

我已经实现了下面的循环，以在新的数据框中一起“发送”类似的记录，但它无法正常工作，我尝试了一些变体，但还没有任何效果。

# create new database
newDB <- data.frame(matrix(ncol = ncol(dat), nrow = 0))
colnames(newDB) <- names(dat)
newDB <- as_tibble(newDB)

for(i in 1:nrow(dat))
{
  # print(dat$title[i])

  for(j in 1:nrow(dat))
  {
    print(dat$title[i])
    print(dat$title[j])
    # score <- jarowinkler(dat$title[i], dat$title[j])

    if(dat$title[i] != dat$title[j]
       &&
       compareJW(dat$title[i], dat$title[j], 0.75))
    {
      print("if")

      # newDB <- rbind(newDB, 
      #                dat$title[i],
      #                dat$title[j])
    }
    else
    {
      print("else")
      # newDB <- rbind(newDB, dat$title[i])
    }
  }
}

（我已在循环中插入打印“以查看发生了什么”）

可重现的数据：

dat <- 
structure(list(title = c("lymphoedema clinic", "zostavax shingles vaccine", 
                         "xray operator", "workplace mental health wellbeing workshop", 
                         "zostavax recall toolkit", "xray meetint", "workplace mental health and wellbeing", 
                         "lymphoedema early intervenstion", "lymphoedema expo", "lymphoedema for breast care nurses", 
                         "xray meeting and case studies", "xray online examination", "xray operator in service paediatric extremities"
)), row.names = c(NA, -13L), class = c("tbl_df", "tbl", "data.frame"
))

请问有什么建议吗？ 编辑：我还想要一个名为“group”的新索引列，如下所示：

> dat
# A tibble: 13 x 1
index   group    title                                          
                 <chr>                                          
 1       1   lymphoedema clinic   
 8       1   lymphoedema early intervenstion                
 9       1   lymphoedema expo                               
10       1   lymphoedema for breast care nurses                             
 2       2   zostavax shingles vaccine 
 5       2   zostavax recall toolkit                                
 3       3   xray operator                                  
 6       3   xray meetint     
11       3   xray meeting and case studies                  
12       3   xray online examination                        
13       3   xray operator in service paediatric extremities
 4       4   workplace mental health wellbeing workshop                                  
 7       4   workplace mental health and wellbeing          

恐怕我从未尝试过RecordLinkage，但如果您只是使用 Jaro-Winkler 距离，那么使用以下命令对相似的字符串进行聚类也应该相当容易stringdist包裹。使用您的dput above:

library(tidyverse)
library(stringdist)

map_dfr(dat$title, ~ {
    i <- which(stringdist(., dat$title, "jw") < 0.40)
    tibble(index = i, title = dat$title[i])
}, .id = "group") %>%
    distinct(index, .keep_all = T) %>% 
    mutate(group = as.integer(group))

解释: map_dfr迭代中的每个字符串dat$title，提取由以下计算得出的最接近匹配的索引stringdist（受 0.40 约束，即您的“阈值”），使用索引和匹配项创建一个 tibble，然后将这些 tibbles 与group与原始字符串的整数位置（和行号）相对应的变量。distinct然后根据重复项删除任何簇重复项index.

Output:

# A tibble: 13 x 3
   group index title                                          
   <int> <int> <chr>                                          
 1     1     1 lymphoedema clinic                             
 2     1     8 lymphoedema early intervenstion                
 3     1     9 lymphoedema expo                               
 4     1    10 lymphoedema for breast care nurses             
 5     2     2 zostavax shingles vaccine                      
 6     2     5 zostavax recall toolkit                        
 7     2    11 xray meeting and case studies                  
 8     3     3 xray operator                                  
 9     3     6 xray meetint                                   
10     3    12 xray online examination                        
11     3    13 xray operator in service paediatric extremities
12     4     4 workplace mental health wellbeing workshop     
13     4     7 workplace mental health and wellbeing          

一个有趣的选择是使用tidytext with widyr按单词进行标记并根据相似度计算标题的余弦相似度words，而不是上面的字符。