Tracing correct words from Jumbled words using machine learning

AI Thread Summary
Machine learning can potentially trace correct words from jumbled letters, but simpler methods like permuting letters and querying a dictionary may suffice. Users express frustration with existing spell checkers and auto-correct features that often misinterpret or replace intended words. The discussion highlights concerns about the limitations of machine learning in this context, suggesting it may not significantly improve upon current solutions. There is skepticism about the necessity of machine learning for this task, as traditional algorithms could achieve similar results. Overall, the conversation emphasizes the need for more user-friendly and accurate text correction tools.
akerkarprashant
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Tracing correct words from Jumbled words using machine learning prediction, search algorithms.
Can we trace all correct words from Jumbled words using machine learning prediction, search algorithms?

https://builtin.com/machine-learning/nlp-machine-learning

Input Dataset : Jumbled words.

Jumbled word example: oolp

Output : pool, loop, polo.
 

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Not sure you’d need machine learning to do this. I’d permute the letters and query a dictionary to determine if it’s a valid word.
 
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YIKES! Not another aggressive spell checker.

Given a set of scrambled letters, it may be possible to find a long list of dictionary words. So the spell checker chooses the one it "thinks" best from the list and replaces my text. Or the machine learning checker chooses the most common word from its training data and replaces my text. It is so frustrating to have all the spell checkers over the years refuse to allow me to type my own name -- Dick. :mad:
 
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Isn't this just a slightly inferior version of that auto-correct/complete feature present in most phone messaging applications?
 
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