Again, all that proves is they need more detailed information over a longer period of time to show all the details on the "trends" page than to just reflect the trend in auto-complete.
It could be, it depends on how it's implemented behind the scenes to be honest.
The autocomplete feature on most search engines is usually implemented as a digital trie of some sort, probably a burst trie because people are typing one letter at a time: https://neuraldump.wordpress.com/tag/burst-trie/
Each of the 'leafs' of the tree has a speculative predictive algorithm that based on the web crawl. These days it's usually a semi-supervisted machine learning algo.
Trends is mostly based on what people actually search for. They need to press return. Different data structure. It's a trend of what people receive a ranked list of result for, not a what people are typing. Usually you can tell such things by taking letters from completely unrelated unicode tables.
source: this is how a basic information retrieval system is taught in computer science and based on my own interpretation based on my experience in search engine optimization over the last few decades. I could be totally off the mark.
The only info needed for auto-complete is the term itself. "crazy times carnival incident". Is it really that hard to imagine they'd need more data over a longer period of time for interest over time, interest by region, related topics, and related queries? And then possibly even more time to properly compile that information into their charts?
All this proves is that Google needs more information for trends than they do for auto-complete.
I have never searched for anything even remotely related to carnivals or crazy times and I got this
https://imgpile.com/i/7SMZeL
Again, all that proves is they need more detailed information over a longer period of time to show all the details on the "trends" page than to just reflect the trend in auto-complete.
It could be, it depends on how it's implemented behind the scenes to be honest.
The autocomplete feature on most search engines is usually implemented as a digital trie of some sort, probably a burst trie because people are typing one letter at a time: https://neuraldump.wordpress.com/tag/burst-trie/
Each of the 'leafs' of the tree has a speculative predictive algorithm that based on the web crawl. These days it's usually a semi-supervisted machine learning algo.
Trends is mostly based on what people actually search for. They need to press return. Different data structure. It's a trend of what people receive a ranked list of result for, not a what people are typing. Usually you can tell such things by taking letters from completely unrelated unicode tables.
source: this is how a basic information retrieval system is taught in computer science and based on my own interpretation based on my experience in search engine optimization over the last few decades. I could be totally off the mark.
I am not defending Google but that does make sense.
The only info needed for auto-complete is the term itself. "crazy times carnival incident". Is it really that hard to imagine they'd need more data over a longer period of time for interest over time, interest by region, related topics, and related queries? And then possibly even more time to properly compile that information into their charts?