R - 文档术语矩阵，以逗号分隔的文本列条目

Question

我有一个数据框，其中包含一个由字符串（project_skills）组成的列，表示某个作业（job_id）提供的技能。我想为每个工作分割这个字符串，以获得工作所提供技能的向量，然后创建一个文档术语矩阵来表示某项工作所提供的技能（从所有可能的技能中提取）。

我有以下数据框：

job_id           project_skills
107182           CSS,HTML,Joomla,PHP
108169           XTCommerce,Magento,Prestashop,VirtueMart,osCommerce
112969           Google Search Console,Google Analytics,Google Webmaster Central,C++,Java,C#
114660           Marketing,Email Marketing
118686           PHP

结果应该看起来像这样（这基本上是一个带有逗号分隔短语的文档术语矩阵：

        project_skills
job_id  CSS   HTML   PHP   Google Search Console   Google Analytics   Java ...
107182  1     0       0 ...         
108169  0     0       0     0                       0         
112969  0     0       0     1                       1 ...         
114660  0     0       0 ...            
118686  0     0       1 ...

我尝试过以下方法：

df <- data.frame(job_id = c(107182, 108169, 112969, 114660, 118686), project_skills = c("CSS,HTML,Joomla,PHP", "XTCommerce,Magento,Prestashop,VirtueMart,osCommerce", "Google Search Console,Google Analytics,Google Webmaster Central,C++,Java,C#", "Marketing,Email Marketing", "PHP"))

corpus <- Corpus(VectorSource(df$project_skills))
corpus <- tm_map(corpus, function(x) {
PlainTextDocument(
    strsplit(x,"\\,")[[1]], 
    id=ID(x)
)
})
inspect(corpus)
dtm <- DocumentTermMatrix(corpus)
as.matrix(dtm)

但不幸的是，这会分割所有单词而不是逗号（例如，Google Search Console应被视为DTM中的一个术语）。

Answer 1

tm（或一些其他文本挖掘包）拆分在单词（空格）上，如果你不检查则倾向于删除标点符号，如+和＃。最简单的选择就是使用strsplit。我使用tidyr和dplyr在下面显示了一个选项。第一组按job_id，然后拆分列。这将创建一个嵌套，当unnested创建一个long data.frame时。在这里，我为每个条目添加值1，其在文档术语矩阵中的作用类似于1。然后扩展为宽格式以获得预期的输出。如果查看结果结构，列名称就是您所期望的，而不显示波浪号（〜）。

library(tidyr)
library(dplyr)

outcome <- df1 %>%
  group_by(job_id) %>% 
  mutate(project_skills = strsplit(project_skills, ",")) %>% 
  unnest() %>% 
  mutate(value = 1) %>% # add 1 for every value
  spread(key = project_skills, value = value) # use fill = 0 if you don't want NA's

head(outcome)
# A tibble: 5 x 18
# Groups:   job_id [5]
  job_id  `C#` `C++`   CSS `Email Marketin~ `Google Analyti~ `Google Search ~ `Google Webmast~  HTML  Java Joomla Magento Marketing
   <int> <dbl> <dbl> <dbl>            <dbl>            <dbl>            <dbl>            <dbl> <dbl> <dbl>  <dbl>   <dbl>     <dbl>
1 107182    NA    NA     1               NA               NA               NA               NA     1    NA      1      NA        NA
2 108169    NA    NA    NA               NA               NA               NA               NA    NA    NA     NA       1        NA
3 112969     1     1    NA               NA                1                1                1    NA     1     NA      NA        NA
4 114660    NA    NA    NA                1               NA               NA               NA    NA    NA     NA      NA         1
5 118686    NA    NA    NA               NA               NA               NA               NA    NA    NA     NA      NA        NA
# ... with 5 more variables: osCommerce <dbl>, PHP <dbl>, Prestashop <dbl>, VirtueMart <dbl>, XTCommerce <dbl>

Answer 2

有很多解决方案，但strsplit是你的朋友。这正是以下代码中所做的：

library(udpipe)
df <- data.frame(job_id = c(107182, 108169, 112969, 114660, 118686), project_skills = c("CSS,HTML,Joomla,PHP", "XTCommerce,Magento,Prestashop,VirtueMart,osCommerce", "Google Search Console,Google Analytics,Google Webmaster Central,C++,Java,C#", "Marketing,Email Marketing", "PHP"), 
                 stringsAsFactors = FALSE)
dtm <- document_term_frequencies(x = df$project_skills, document = df$job_id, split = ",")
dtm <- document_term_matrix(dtm)
colnames(dtm)
 [1] "C#"                       "C++"                      "CSS"                      "Email Marketing"         
 [5] "Google Analytics"         "Google Search Console"    "Google Webmaster Central" "HTML"                    
 [9] "Java"                     "Joomla"                   "Magento"                  "Marketing"               
[13] "osCommerce"               "PHP"                      "Prestashop"               "VirtueMart"              
[17] "XTCommerce"              
rownames(dtm)
[1] "107182" "108169" "112969" "114660" "118686"
dim(dtm)
[1]  5 17