Infrrd is a leading automated data extraction & image recognition company that uses machine Intelligence and AI to solve analytics and automation related problems for their customers. Their pre-packaged, ready to use AI solutions provide companies a headstart at solving AI challenges.
Infrrd's high accuracy document digitizing and automated data capturing OCR solutions improve cost efficiencies in the business environment, reducing the need for manual document sorting and manual data entry. Infrrd's OCR & image recognition solutions have been providing substantial returns on the original investment by different industries like retail, finance, vendor management systems, back office & BPOs etc. The machine learning algorithms learn intuitively and scan images invoices, receipts, business documents and handwritten documents with ease.
Based on our record, FuzzyWuzzy seems to be more popular. It has been mentiond 11 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Do fuzzy matching (something like fuzzywuzzy maybe) to see if the the words line up (allowing for wrong words). You'll need to work out how to use scoring to work out how well aligned the two lists are. Source: over 1 year ago
Convert the original lines to full furigana and do a fuzzy match. (For reference, the original line is 貴方がこれまでに得てきた力、存分に発揮してくださいね。) You can do a regional search using the initial scene data (E60) first, and if the confidence is low, go for a slower full search. Source: over 1 year ago
It's now known as "thefuzz", see https://github.com/seatgeek/fuzzywuzzy. Source: almost 2 years ago
You can have a look at this library to use fuzzy search instead of looking for plaintext muck: https://github.com/seatgeek/fuzzywuzzy. Source: over 2 years ago
To deal with comparing the string, I found FuzzyWuzzy ratio function that is returning a score of how much the strings are similar from 0-100. Source: almost 3 years ago
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