Text 术语对和短语的tm_术语_分数错误

尝试使用tm_term_score为行中的文本将术语短语或术语对评分为1或0会出现以下错误：

c1 <- Corpus(VectorSource(r1))
inspect(c1)
inspect(c1[2])
cleanR1 <- tm_map(c1, removeWords, stopwords('english'))
cleanR1 <- tm_map(cleanR1, content_transformer(tolower))
cleanR1 <- tm_map(cleanR1, removeWords, c("re", "ve", "ahha"))   
cleanR1 <- tm_map(cleanR1, removePunctuation)
cleanR1 <- tm_map(cleanR1, removeSpecialChars)
cleanR1 <- tm_map(cleanR1, removeNumbers)
cleanR1 <- tm_map(cleanR1,removeWords,stopwords('en'))
cleanR1 <- tm_map(cleanR1,stripWhitespace)
cleanR1 <- tm_map(cleanR1,stemDocument)
cleanR1 <- tm_map(cleanR1, PlainTextDocument)

tm_term_score(cleanR1, terms, FUN = slam::row_sum) 

---

c1您需要将
明文文档
、由
termFreq
返回的术语频率或
TermDocumentMatrix
传递给
tm\u term\u score
的第一个参数，而不是语料库

使用术语文档矩阵的示例：

tdm <- TermDocumentMatrix(cleanR1)
tm_term_score(tdm, terms, FUN = slam::row_sum)

tdm我正在使用TermDocumentMatrix，但仍然得到相同的错误。tdf\u arrTerms我不明白你们想用sapply做什么，直接把你们的术语传给
tm\u term\u score
是的。我明白了。tm文档中提供了sapply样本。谢谢