Aori has a feature that helps you to find closely related words to the keywords entered, to expand the list and help the user find more relevants words.
The suggestions use a bit of machine learning to look at the words and phrases entered in the keyword banks to find other words relevant for keyword building.
Aori can also suggest whole phrases by parsing the lexical structure of the phrase entered. Aori doesn't change the root word in a phrase, but it will suggest variations for secondary words (try "cat food" for example).
This is a quick way to add more words to your keywords banks. We suggest words that we think are "close" or related to the ones already in a bank. It's sometimes difficult to determine the exact meaning of a word (e.g. "test" could be a math test or a medical test). In that case it's useful to provide more context by dismissing the words that are wrong for your use case. Our machine learning algorithm will adapt the suggestions accordingly.
To power these suggestions, Aori is using a database with 1.1 million entries that contains words and phrases. Here is a simple example:
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