Extracts top keywords from a document-feature matrix using TF-IDF weighting.
Usage
extract_keywords_tfidf(dfm, top_n = 20, normalize = FALSE)
Arguments
- dfm
A quanteda dfm object
- top_n
Number of top keywords to extract (default: 20)
- normalize
Logical, whether to normalize TF-IDF scores to 0-1 range (default: FALSE)
Value
Data frame with columns: Keyword, TF_IDF_Score, Frequency
Examples
if (FALSE) { # \dontrun{
library(quanteda)
corp <- corpus(c("text analysis", "data mining", "text mining"))
dfm_obj <- dfm(tokens(corp))
keywords <- extract_keywords_tfidf(dfm_obj, top_n = 5)
print(keywords)
} # }
