text_mining_example_with_korean_songs
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library(bitops) library(RCurl) library(KoNLP) library(rJava) library(tm) library(wordcloud) library(XLConnect) setwd ("D:/Users/Hyo/Clouds/Cs-Ds/CS/MusicStudy") rm(list=ls()) music<- file.path("mm.xlsx") music90s <- readWorksheetFromFile(music, sheet="1990s") lyrics<- Corpus(VectorSource(music90s$lyrics)) result.text <- lyrics removeTwitSign <- function(x) { gsub("@[[:graph:]]*","",x) } # may not be used in this case removeURL <- function(x) { gsub("http://[[:graph:]]*","",x) } # may not be used in this case removeEnter <- function(x) { gsub("\n","",x) } exNouns <- function(x) { paste(extractNoun(x), collapse=" ")} # NA -> "" 로 변환 result.text[is.na(result.text)] <- "" useSejongDic() mergeUserDic(data.frame(c( "개여울", "고운정", "못잊어", "내마음", "가시내", "꽃가마", "내곁", "윙크", "못잊어서" ), c("ncn"))) result_nouns <- sapply(result.text, removeEnter) result_nouns <- sapply(result.text, exNouns) myCorpus <- Corpus(VectorSource(result_nouns)) myCorpus <- tm_map(myCorpus, removePunctuation) myCorpus <- tm_map(myCorpus, removeNumbers) myCorpus <- tm_map(myCorpus, tolower) myStopwords <- c(stopwords('english'), "rt") myCorpus <-tm_map(myCorpus, removeWords, myStopwords) inspect(myCorpus[1:5]) myTdm <- TermDocumentMatrix(myCorpus, control=list(wordLengths=c(1,Inf))) mat <- as.data.frame(as.matrix(myTdm)) write.table(mat, file="_lyrics_90s1.txt", col.names=FALSE, row.names=TRUE,sep="\t") myTdm2 <- TermDocumentMatrix(myCorpus, control=list(wordLengths=c(2,Inf))) mat2 <- as.data.frame(as.matrix(myTdm2)) write.table(mat2, file="_lyrics_90s2.txt", col.names=FALSE, row.names=TRUE,sep="\t") par(mfrow = c(1,2)) pal <- brewer.pal(8,"Dark2") # 폰트 세팅. 띄어쓰기나 대소문자에 민감하다는 점에 주의 # 맑은고딕 : windowsFonts(malgun=windowsFont("맑은 고딕")) # 나눔고딕 : windowsFonts(malgun=windowsFont("나눔고딕")) windowsFonts(malgun=windowsFont("맑은 고딕")) m <- as.matrix(myTdm) v <- sort(rowSums(m), decreasing=TRUE) myNames <- names(v) d <- data.frame(word=myNames, freq=v) wordcloud(d$word, d$freq, scale=c(7,0.8), min.freq=3, random.order=F, rot.per=.1, colors=pal, family="malgun") m2 <- as.matrix(myTdm2) v2 <- sort(rowSums(m2), decreasing=TRUE) myNames2 <- names(v2) d2 <- data.frame(word=myNames2, freq=v2) wordcloud(d2$word, d2$freq, scale=c(7,0.8), min.freq=3, random.order=F, rot.per=.1, colors=pal, family="malgun")
text_mining_example_with_korean_songs.1481066398.txt.gz · Last modified: 2016/12/07 07:49 by hkimscil