251–260 of 639 posts
Earlier quoted context omitted.
I expect most users genuinely looking for such a product would just search "plain shirt"
Like I said in another comment, this yields plenty of results that are not in fact plain shirts. Try for yourself on Amazon or Google.
hm, 'without' is a tough one. You're not looking for a zebra without stripes. You're looking for a horse.
Earlier quoted context omitted.
That is an inclusive search though. What if the user actually wanted to simply exclude stripes but wanted to see polka dots and paisley?
I think that is probably not a common enough use case to optimize for. Additionally it would be easy for a user in that position to just search "shirt" and ignore the occasional striped one, or to search "polka dot" and "paisley" seperately
"birds without flight"
"cars without wheels"
"cats without tails"
"dogs without hair"
"intersections without lights"
"poems without rhyme"
"shirts without collars" (also "sleeves", "shoulders", "buttons", "logos", "pockets", and more)
Counterexample: https://www.google.com/search?client=firefox-b-d&q=Doctors+W...
The point of this isn't asking how to apply boolean search operators, it's showing that the largest AI-focused companies in the world absolutely suck at NLP.
Why would you really apply NLP to a search engine though? Generally speaking a weighted keyword search is good enough 95% of the time and requires significantly less resources to perform.
"Shirts"
"Polka dot shirts"
"Floral shirts"
"Wikipedia list of clothing patterns"
"Houndstooth shirts"
Earlier quoted context omitted.
I think that is probably not a common enough use case to optimize for. Additionally it would be easy for a user in that position to just search "shirt" and ignore the occasional striped one, or to search "polka dot" and "paisley" seperately
That sounds like a lot of repetitive searching. I wonder if we could get a computer to do that for us.
Why should it not be possible to solve this with statistical methods? The model just needs to be able to understand the important meaning of "no" in here, in the context of the whole sentence. I would guess that most modern NNs from the NLP area (Transformer or LSTM) would be able to correctly differentiate the meaning. The problem is, I think there is no fancy NN (yet) behind Google search, and the other web searche…