I used to refer a lot of documents and I was facing disorganization issue with the documents. then I did some research regarding this issue and find out many of my friends and teachers suffer with same issues. Then I started refering to multiple solution for this problems. And found out this one practical implementation.
Too Many Documents under a single directory not only confuses the user, but it is also a time consuming job for a User to find a particular file at very efficient time. Documents needs to be settled at a specific address from where it can be extracted easily.
That classifies the document into various classes according to its content. Currently available Classes are Art, Science & Technology, Finance, Government & Politics, and Health. It analyses and handles the documents on a large scale .
Using React, we have built web-app to provide user interface and collect documents. Then using flask, we have built server to actually use the ML model on data. After it will transfer documents from web-app to server. We will extract features from documents and pass it to ML model and then it will generate category output.
It was really got messy, when we started implementing server. But make it out of it.
While building a project, we should always consider its scalability in future.