What you are asking for might be possible by writing your own program (e.g. in Python) to access the Google Scholar API. In fact it would make a good assignment for a Python programming / Text processing class. But unless you are a programmer with extra time on your hands, you shouldn't attempt it.
For what it's worth, I almost never use "related articles" feature of Google Scholar. The few times I did use it, there wasn't always such a close relationship, and it certainly didn't bring up the articles that I saw as most related.
I don't think there's any substitute for reading the papers, at least the important ones, to find the most salient related papers. I do this both through direct citations and also by finding key terms that I use for new Google Scholar searches.
A
in my library. When I click on "related articles" button, let's say, there is an articleX
on the second page of related articles. When I click on the articleB
in my library, let's assume,X
pops up on the third page. Continuing on the articles in my library,X
reoccurs on several occasions, on either first or second, or third page. So, is there any way that such system will tell me that "dude,X
kind of important! I can see it's related to all of your articles somehow. Better check that out!"?