Define words-red flags in comment, written by user

[Alla_Hordieieva]

Dear all,

Could you please help me with the following task: I have a business process that is already realised in Python. I need to rewrite it in Alteryx. There is one field in data set, that is filled in by users manually (comments). I need to find special words (red flags) in these comments. The problem is that these words could be written with mistakes, for example, "backfil" instead of "backfill". In Python, it is realised by the NLTK library and the stemmer function. Is it possible to realise this with Alteryx functions? I tried to implement the piece of code from Python into my Alteryx workflow, but without success. There is no text mining functions in my company.

Thank you in advance.

[MelGibson]

If you have Alteryx Intelligence Suite, you can use the Python tool to integrate your existing Python code directly into your Alteryx workflow. This way, you can leverage the NLTK library and stemmer function as you did in your original Python implementation. I do not have an example for you, maybe someone else can provide that. You could also create a reference list of misspelled words (if you have historical data) and perform a fuzzy match.  You would need to do a clean up of your incoming data (remove punctuation, reduce case to lowercase, etc) this doesn't have to be your output, you can create a new field. That way you remove any possible mismatches. For example, someone inputs inc. and some just inputs inc then you would have a match. Best of luck.