Hey this is an interesting idea. How would it be done though?

For example I've noticed certain similarities across classical statistics, Machine Learning and digital signal processing. But they all seem to come at it from different angles, and they often use different terminology. Sometimes a field will rediscover something discovered elsewhere a long time ago, eg the trapezium rule.

even worse, a field will take term from another field and misuse it enough such that "wrong" definition" becomes the default definition

Slightly relevant classic: https://fliptomato.wordpress.com/2007/03/19/medical-research...

That sounds super interesting! The results will depend upon the kind of information this database provides about each paper. We don't know yet the kind of processing each paper goes through and the quality of the "description" in the database. Assuming that it is good enough, this would be a really interesting project to work on.

Here we return to models based on LaTeX stuff and the lack of development in this OCR area to generate that index.

One of my colleagues, Richard Zanibbi, leads the Document and Pattern Recognition Lab[0] here at the Rochester Institute of Technology. They're doing a lot of interesting work on formula recognition and search.

[0] https://www.cs.rit.edu/~dprl/

I just finish looking into their projects. They are very promising. I don't why they don't try to engage with OOS community. They can get their models used in a manner that can help many people and will open many ways to use their work.

Where is "here"?

This discussion!

Sign me up for that!

This is an amazing idea !

Brilliant. Let us dig in!