BERT is much more sophisticated than the "bag of words" approach. BERT looks at the order of words in our content, the parts of speech, and any word entities that appear. It's powerful and can be trained to do a lot of things, including question answering and named entity recognition - certainly more advanced than basic word frequency.
However, BERT still needs to see the words on the page thailand mobile database to work, and word frequency is just a basic summary of this. Now, word position and part of speech are more important. We can't just randomly throw the words we found in the gap analysis on the page.
In order to make our content unambiguous to machines, we first need to make it unambiguous to users. Reducing ambiguity in our writing is all about choosing words that are specific to the topic we are writing about. If our writing uses a lot of generic verbs, pronouns, and non-topic adjectives, then our content will not only be boring, but also difficult to understand.