I was just wondering, Is there any possibility that we train neural networks (may be
RNN) on different formats of dates (with multiple examples in each format to expand its learning) and then ask the neural net to extract a close match of date in a
All I need is a
Machine learning algorithm to do
pattern matching instead of using
regex. Can this be implemented?
If so, Please provide me an idea of implementation or any already working solution (
R) is also fine.
Update: Added my problem statement for better understanding
My Input text file (input.txt) with different formats of dates (Say, I have some thousands of examples for each format) will be as following: (Say, I will only be expecting these formats of data in the raw file)
13/08/1993 23/09/2016 24/12/1992 ... 13-08-1993 23-09-2016 24-12-1992 ... 13-Sep-1993 23-Sep-2016 24-Dec-1992 ... Some other formats
RAW TEXT file is given below: (It is just a OCR Extracted info from a receipt)
ROCKET MEALS 23/09/2015 RECEIPT ID: #294055 Shop: #1 ITEM QTY PRICE French Fries 33.26 Coca Cola 22.4 SUB TOTAL: 95.66 Tax: + 6.45 TOTAL: 102. 1 THANK YOU - VISIT AGAIN
PS: I have already used
regex for this but, actually I am curious to know how to train such a network and how it understands the patterns?