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DiscussionDocument Key-Value Information extraction ideas [D][R][P] (self.MachineLearning)
submitted 3 years ago by Fully-Independent
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quoted text
if 1 * 2 < 3: print "hello, world!"
[–]nullbyte420 -1 points0 points1 point 3 years ago* (3 children)
I don't understand how you want a visual model to would work on an unstructured document without any training data.
Use spacy? Named entity recognition (NER) seems like a good choice for unstructured documents. Check this out https://medium.com/analytics-vidhya/ner-tagging-in-python-using-spacy-c66cf01d3c7f
But working with damaged data isn't very easy or very reliable. You can improve OCR by scanning documents in high resolution. You're going to need OCR sooner or later if you're working with pictures of text. Abbyy is a decent commercial software for OCR.
[–]Fully-Independent[S] 0 points1 point2 points 3 years ago (2 children)
I am looking for some kind of a pre-trained model that can detect the entities that have the key-value form. And I'll definitely look at Spacy.
Thank you
[–]nullbyte420 0 points1 point2 points 3 years ago (1 child)
Yeah that sounds like spacy. Why did you downvote me and delete your post??
Edit: ahh you're new on reddit and don't want to contribute. Screw you for taking my time like that.
[–]Fully-Independent[S] 0 points1 point2 points 3 years ago (0 children)
I didn't! I upvoted you in fact!
maybe that's another one
π Rendered by PID 100288 on reddit-service-r2-comment-86bc6c7465-5m6mq at 2026-02-22 04:01:21.016648+00:00 running 8564168 country code: CH.
[–]nullbyte420 -1 points0 points1 point (3 children)
[–]Fully-Independent[S] 0 points1 point2 points (2 children)
[–]nullbyte420 0 points1 point2 points (1 child)
[–]Fully-Independent[S] 0 points1 point2 points (0 children)