我一直在研究 R 中 {tm} 包的许多在线示例,试图创建一个 TermDocumentMatrix。创建和清理语料库非常简单,但是当我尝试创建矩阵时总是遇到错误。错误是:
UseMethod("meta", x) 中的错误:没有适用于 'meta' 的适用方法应用于“character”类的对象另外:警告消息:在 mclapply(unname(content(x)), termFreq, control) 中:所有计划的核心在用户代码中遇到错误
例如,这里是 Jon Starkweather 的文本挖掘示例中的代码。提前为这么长的代码道歉,但这确实产生了一个可重现的例子。请注意,错误出现在 {tdm} 函数的末尾。
#Read in data
policy.HTML.page <- readLines("http://policy.unt.edu/policy/3-5")
#Obtain text and remove mark-up
policy.HTML.page[186:202]
id.1 <- 3 + which(policy.HTML.page == " TOTAL UNIVERSITY </div>")
id.2 <- id.1 + 5
text.data <- policy.HTML.page[id.1:id.2]
td.1 <- gsub(pattern = "<p>", replacement = "", x = text.data,
ignore.case = TRUE, perl = FALSE, fixed = FALSE, useBytes = FALSE)
td.2 <- gsub(pattern = "</p>", replacement = "", x = td.1, ignore.case = TRUE,
perl = FALSE, fixed = FALSE, useBytes = FALSE)
text.d <- td.2; rm(text.data, td.1, td.2)
#Create corpus and clean
library(tm)
library(SnowballC)
txt <- VectorSource(text.d); rm(text.d)
txt.corpus <- Corpus(txt)
txt.corpus <- tm_map(txt.corpus, tolower)
txt.corpus <- tm_map(txt.corpus, removeNumbers)
txt.corpus <- tm_map(txt.corpus, removePunctuation)
txt.corpus <- tm_map(txt.corpus, removeWords, stopwords("english"))
txt.corpus <- tm_map(txt.corpus, stripWhitespace); #inspect(docs[1])
txt.corpus <- tm_map(txt.corpus, stemDocument)
# NOTE ERROR WHEN CREATING TDM
tdm <- TermDocumentMatrix(txt.corpus)