Genetic Algorithms within Evolved Web Search

I haven't sat down to discuss how the big internet search engines like Google do. The essence of this writing is to tie the search engine in a systematic way that we use in the daily activities of ordinary people. By doing so, we will be able to use all the information that is known about it.
. I wrote a post on how to search for literature. Here's how to translate that approach into any case:

“Suppose I am allowed to solve a problem. I pick up a few keywords from the problem and do a Google search with it. From the results I get, I pick and choose the new keywords. In this way, I continue to search until I find something better. ”

How does this approach go with the genetic algorithm? Genetic algorithms are key but are involved with the deception of our society and the animal kingdom. You may have heard the phrase 'survival of the fittest'. This means that nature does not like weak children. Therefore, at every generation, vulnerable creatures fall and the better species continue to survive. Now tell me you've got to catch up with the weird web search?

A genetic algorithm is a systematic method that simulates the above process. Wikipedia has two beautiful articles on it, namely genetic algorithms and genetic programming.

You must understand by now that this web search is an application of genetic algorithms. For your convenience, I am writing another reputable web search method here:

1. Choose some keywords that are relevant to your content but may be random. Search for these queries
2. Choose the best ones from the results you get. Choose some keywords again from the best results.
3. Search again with these new keywords until you get exactly what you want
4. If you can't find it for a while, stop.

Like the genetic algorithm, this also has some problems. If your starting keywords are not good, you may never find what you need. Again, if you do not like the result every time, you will not find anything in your whole life. On the contrary, if you like all the results, in the end, you will end up with a lot of unnecessary information.