tf-idf.R

# tf-idf implementation in R

#### TF-IDF for Products ###
# Calculate frequency of words for each skincare product
product_words <- data %>% 
  select(Product,ReviewContent)%>%
  tidytext::unnest_tokens(word, ReviewContent) %>%
  count(Product, word, sort = TRUE) %>%
  ungroup()

# Calculate the amount of times a word appears in a document
total_words <- product_words %>%
  group_by(Product)%>%
  summarize(total_words = sum(n))

#join total and n
product_words <- left_join(product_words, total_words)

# compute df, idf
product_words <- product_words %>%
  tidytext::bind_tf_idf(word, Product, n)

# arrange dataset by tf_idf
product_words %>%
  select(-total_words) %>%
  arrange(desc(tf_idf)) 
  
### TF-IDF for "Query" user input ###
# Function to compute tf_idf 
query_tf_idf <- function(tags_list, words_data){
  n <- length(tags_list)
  word <- data.frame(word = tags_list)
  tf <- rep(1/n,n)
  dt <- cbind(word,tf)
  selected_bag <- unique(select(words_data,word,idf))%>%filter(word %in% dt$word)
  dt <- left_join(dt,selected_bag)
  dt$tf_idf <- dt$tf * dt$idf
  dt <- dt[order(word),]
  return(dt)
}