I have a sample use case, where user will give us a xls file with some location data. Where may be location information is given in different ways , sometime its IATA code, sometimes its standard abbreviation, sometimes they use own abbreviation or sometime just a short name of that location too and it can be in any format.
Now job of my application will take XLS as input and convert it my standard. By “My Standard” I mean to say I have a complete data set with almost all location in my database.
So, In simple words it will map user given input to my standard location name, which stored in my DB.
My model should have that capability also , where may be , if for any location it not able to map with any data in my location DB , I will train the model with that data. My "train" I mean to say I will map that user input with any location of master data.
Next time onward, if model receive same input, it should be able to map it with my master data, as per my last training.
Sample User Input and inference for location:
Can any one suggest any suitable solution this use case , Just a outline of though would be very helpful and will be appreciated.
I tried with fuzzywuzz to solve this problem, But that did not help me much to solve the use case completely.