I have a problem moving from a tm object to a koRpus object. I have to normalize a corpus with tm tools, lemmatize the results with koRpus and return to tm to categorize the results. In order to do this I have to transform the tm object into a R dataframe, which I then transform into an excel file, then into a txt file, and finally into a koRpus object. This is the code:
#from VCORPUS to DATAFRAME
dataframeD610P<-data.frame(text=unlist(sapply(Corpus.TotPOS, `[`, "content")), stringsAsFactors=F)
#from DATAFRAME to XLSX
#library(xlsx)
write.xlsx(dataframeD610P$text, ".\\mycorpus.xlsx")
#open with excel
#save in csv (UTF-8)
#import in KORPUS and lemmatization with KORPUS/TREETAGGER
tagged.results <- treetag(".\\mycorpus.csv", treetagger="manual", lang="it", sentc.end = c(".", "!", "?", ";", ":"),
TT.options=list(path="C:/TreeTagger", preset="it-utf8", no.unknown=T))
Then I need to do it all backwards to get back to tm. This is the code:
#from KORPUS to TXT
write.table(tagged.results@TT.res$lemma, ".\\mycorpusLEMMATIZED.txt")
#open with a text editor and formatting of the text
#from TXT to R
Lemma1.POS<- readLines(".\\mycorpusLEMMATIZEDfrasi.txt", encoding = "UTF-8")
#from R object to DATAFRAME
Lemma2.POS<-as.data.frame(Lemma1.POS, encoding = "UTF-8")
#from DATAFRAME to CORPUS
CorpusPOSlemmaFINAL = Corpus(VectorSource(Lemma2.POS$Lemma1.POS))
Is there a more elegant solution to do this without leaving R? I’d really appreciate any help or feedback.
BTW, does anyone know how to ask tm which document inside a VCorpus contains a specific token? I usually transform the corpus into a dataframe to identify the document. Is there a way to do this in tm?
