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Discussion on: Google annoys me insanely.

joelbonetr profile image
JoelBonetR • Edited on

It's a double edge sword. What about looking for a mask for coronavirus and being spammed with the movie, thematic forums, merchandising and fandom posts about it just because you searched something about Jim Carrey before?
Then you could fall on a non-return situation where you can't get off.

Google uses your recent searches and what it knows about you for offering content to you but also uses social context and searches from people near you or with similar not-nominal features, also it trains itself with user interaction - it means if a high percentile of users who searched the same (or similar) got the result on the website A, it will offer you this website A because it's probable that you find what you want-, moreover it score websites with other metrics that leads you to a better overall user experience.

I think they did a good work polishing the search engine and what you want to achieve is provided by a conversation with a "virtual assistant" that has been trained with NLP (natural language processing) that is a branch of machine learning, these are two different tools and two different concepts that solves two different needs.

Also the big G is working on that to implement it along Google Assistant, which is a better place to use it, and always you need a way to stop the current conversation and start again from zero for not falling into the death spiral mentioned above 😂

Let's unravel the two situations for further details:

NLP Assistant vs Search Engine

NLP Assistant

Imagine you are bored at home and you linked your Google Assistant to your TV (it must be a requirement huh?)

You ask your Google Assistant something like "How old is Jim Carrey?"
It will tell you "58 years"
then you remember the movie and ask "I want to watch Mask"

with that data it should be able to point you to the movie:

  1. because you asked to watch something.
  2. because you both were talking about Jim Carrey on THIS conversation.

the workaround is something similar to this simplified example:
It first gets the training:

Then when using it (also training at this point, in fact it's always training):

  1. keep current conversation data.
  2. figure out if the current question or statement has something to be with the latest one, if not search for the one before and so on.
  3. Use the training results it already has to figure out which answer to your question/statement is more "true" (actually it's a value between 0 and 1, - rarely it's 1- so the movie will be scored with something like 0.9 true)
  4. offer the answer to the user.
  5. If user asks again almost the same keep this information for training and recalc the conversation to give a more accurate answer.

Search Engine

On the other hand, when you search on Google Search you must act like a good writer: adding the necessary details for it to figure out what do you mean but not too much for it to being verbose (boring).

If you search "Mask" obviously it will show you masks, because by probability it's more "true" that you want a mask than anything else, because percentiles never lie and it may be a 99% of people that searched for masks to protect against covid or for a peeling mask to deal with the irritation produced by the first ones 😆

If you search "The Mask" it's highly probable that you will be pointed to the movie (because actually this is the name of the movie, you can't expect searching for "Lambs" and crying because you wanted the movie "The Silence of the Lambs").

If it's not the case, of course you can add "movie" to your search and that's all.

Take a look at the official user documentation if you are sometimes in trouble for getting your answer. If you feel this is a bit dumb, take a look at the "Expert search tips" you'll find at the bottom that will help you for sure!

Hope it helps to understand the workaround and the difference of this two technologies :D

sologub profile image
Sologub Author

Very detailed analysis. But what if you try to look towards this tool here:

joelbonetr profile image
JoelBonetR • Edited on

Didn't know about, just tried to search "mask" on it. Still needs to clarify that it's a movie, otherwise you'll be fulfilled with information about what "mask" means and historical data.
Also useless if you want to buy a mask.

I assume this is a tool with pre-defined queries over an elastic search or similar where your clarifications add a string into it, some way of categorization. It could be useful when searching for concepts but that's all, have you find any utility to it? Please tell us what it solves and in which situations it could be useful vs other tools