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I would like to double-check something. Is nGrams the same exact thing as TF-IDF?

That is, if I want a list of the most frequently used keywords (minus stop words) for a keyword phrase that I'm targeting from the Top 10 sites on page 1 of the SERPs (for Google, Bing, and other search engines individually), how do I get to that? Is it just simply go into Full Compare mode, scroll down to nGram section? Or if there is a separate way to get to that.

Since I'm comparing my text content to the top 10 competitors on page 1 of the SERPs, so I can match my text content to their most frequent or important keywords, is there a way to do that within the software, instead of comparing my URL page to theirs?  I would still like to be in an editor mode, so I can tweak the text in real-time while getting the keyword density % to match theirs, this would save time and hassle.

If that feature is not included, can you please consider it in an update.

Also, the Full-Compare mode page can be very long. Is there any jump-to shortcut option at the top somewhere, if not, can you include that too? It would save time scrolling and searching for the desired section.

Thank you! :)


  • nGram is not the same thing as TF-IDF. 
  • SvenSven
    There is a simpler way than loading the full competitor view. Right click on the keyword->nGram Data
    There you also the more details to the TF-IDF.
    Thanked by 1ToyotaMR2
  • In Gram Data view, can the decimals be displayed as percentage for TF (Term Frequency) ?

    Is there a way to filter results by either search engine type, Google or Bing?  (or setup a project to choose either one to get results from)

  • SvenSven
    You better look at the importance column then, I will not change the TF to % sorry.
    Search engine parameters can be change via the options button. You can not mix google with bing...just one search result is displayed here.
  • edited May 12
    There are many tools that measure tf-idf I have used over the years. I have never seen it expressed as a percentage because it is not supposed to represent the concept of “keyword density.”
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