Similarity between two text columns
I have a dataset with two columns indicating company names. I was wondering what is the best way to determine the similarity between the two?
Perhaps, I can pass 3 columns in R/Python and return 4 columns with cosine similarity. Can I do that? A starter code/example would be great?
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https://stackoverflow.com/questions/560709/levenshtein-distance-in-t-sql
Levenshtein distance is a common way of calculating the similarity between two text values (i.e. how many characters would you have to change before they are the same. "cat > rat" = 1, "John > Jon" = 1.
You'll have to rewrite it into MySQL but it can be done. For a workflow like this though, you'll want some sort of process where a user accepts or discards a recommendation which you'll want to accumulate (recursively?) in a lookup table of 'approved matches'.
in my above example, you may not want to automatically accept that John and Jon are the same entry... hence the need for a feedback loop. Domo can of course handle that as a simple webform or more dynamically with a custom app with a polished user interface.
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