A wants to use a 120-question cognitive assessment program in order to define and describe someone’s thinking preferences, according to 4 quadrants (for example analytic, emotional, creative, organised).
They are interested in adding an NLP feature to their assessment and are thus interested in finding a platform that could provide a classifier model. The aim of this classifier would be to:
Diagnose if a piece of free text (answer to an open-ended question) demonstrates high or low preference for a particular quadrant.
Ultimately this classifier should be able to analyse communication (emails, documents, job descriptions)
Identify the words/strings/characteristics in the text that reflect each quadrant.
Be able to use the classifier as en e-mail plugin that would highlight the different words/expression according to the quadrant they represent and suggest recommendations according to the thinking preferences of the recipient of the email.
I was wondering if Amazon Comprehend will meet this requirements for the classifier model because, from what I could see in the FAQs of the service, Comprehend does not support custom models. Could anyone confirm if Comprehend will be a good fit for this use case and, in case it is not, what could be workaround to meet the customer's requirements in the AWS cloud?
