Wow, never thought about how complex of a problem that can really be. To hijack your example: searching for [rust http library] and [clean rust from metal bookshelf] should be completely separate lines of querying but without understanding the full context, appear to have many false similarities (rust, library/bookshelf, 'clean' is a word associated with compiling software, and 'metal' can cause confusing with projects/articles on [bare metal programming with rust])
Google's methods for detecting clustering, or whatever they are using, are so 'clever' I feel like I'm unable to communicate what I want. I feel like I'm arguing with a particularly intelligent and malicious toddler sometimes.
Say I was to ask a toddler to bring me a beer, and they brought me a root beer. I'd be like, "no, bring me a beer, -root."
A normal child would bring me a normal beer, cause that's the only thing in the fridge that has beer in the title without root. The Google child would bring me some sassafras, because sassafras is a root beer, which is a beer, but it doesn't have root in the name.
Annoyed, I turn off safe search, and I say "Bring me a beer, -root -sassafras -sarsaparilla -ginger -cider."
The Google child comes back and says "I couldn't find what you were looking for." I get up off the couch, look in the fridge, and lo and behold it's completely full of beer.
Machine learning is definitely a big part of it, but you can also get surprisingly far with simple bag-of-words models when applied to enough data.