# finding frequency of the terms
findkeyword<-function(text_data){
tdm_data <- tdm(text_data)
stringData<-findFreqTerms(tdm_data,lowfreq = 0)
library(hunspell)
suggest_check<-hunspell_check(stringData)
wrong_str<-stringData[!suggest_check]
correct_str<-stringData[suggest_check]
suggestions<-hunspell_suggest(stringData[!suggest_check])
if(length(suggestions)!=0){
for(d in 1:length(suggestions)){
suggestions[[d]]<-tolower(suggestions[[d]])
}
x<-as.vector(NULL)
y<-as.vector(NULL)
count<-0
fin<-as.vector(NULL)
rec_str<-as.vector(NULL)
big <- big()
big_count<-sapply(gregexpr("\\W+", big), length)
# Replacing wrong with right ones from suggestions
for(i in 1:length(suggestions)){
x<-wrong_str[i]
if(length(suggestions[[i]])!=0){
for(j in 1:length(suggestions[[i]])){
y<-suggestions[[i]][j]
count<-0
a<-adist(x,y)
prob_len <- 1-a/(stringr::str_count(suggestions[[i]][j]))
prob_most <- (stringr::str_count(big,y))/big_count
c <- prob_len * prob_most
fin[j]<-c
y<-as.vector(NULL)
}
rec_str[i]<-suggestions[[i]][which.max(fin)]
fin<-as.vector(NULL)
x<-as.vector(NULL)
}
else{
rec_str[i]<-wrong_str[i]
}
}
str_final<-append(correct_str,rec_str)
}
if(length(suggestions)==0){
str_final<-correct_str
}
return(str_final)
}
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