For basic keyword searches. It’s not uncommon for search users to want inexact equivalencies, synonyms or conceptually close search results. (Search for cold, get back rhinovirus). Every user and use case has different definitions/tolerances of “this term appeared on the page”
It’s a complicated topic, without simple solutions. I wrote about it here.
https://opensourceconnections.com/blog/2018/12/07/synonyms-b...
We can argue whether there is place for more operators, or whether it's better on average for an average user to still be "outsmarted" by the engine, but it's clear what's going on - these aren't exact match results and the results often have zero relevance with what user is looking for precisely because the user knows the specific word WILL appear on the page they need and a page without that word WON'T be what they need. I don't know how much clearer we can be :) It used to work (or seemed to). Now it doesn't. It frustrates some people. That's it.
I've interpreted searches. Database searches, not web pages, but my problems should apply to web search too: For example, a user who types "märz 2019" with quotes might mean that string, in German, or might on the other hand mean that particular month and use the quotes to eliminate february 2019, march 2018, etc. And people enter the exact string they remember in the hope of avoiding a sea of mismatches, but then they either mistype or don't remember quite the right wording.
Don't mess with my search terms! Bring exact matches back! Only show pages that match the search terms!
The amount of automatically created synonyms is getting out of hand, it decided the name of where I work is a synonym for another company in the same business that's 15 miles away
It seems to me the main failing of Google is they have no good way to say "We understood your question, but the answer isn't on the internet".
Instead they just return a set of not very relevant results.
This has been abused many times by using derogatory link texts when linking to politicians web pages.
https://github.com/HTTPArchive/legacy.httparchive.org/blob/m...
You can search for anything in the source-code of pages, using any regex or grep you can imagine.
Obviously running your custom filter logic across every byte of data that has ever existed on the internet is compute heavy... But Google has lots of that!
Do you have an example? Exact match has been working fine for me.
"azure" devops agent "checkout" "freeze"
I'm obviously searching for something very specific here, and Google helpfully decided to show me results omitting "freeze" and "checkout" so I had to quote them.
I also notice that it looks like Google thinks that check-up is the same thing as checkout, which in context are not synonyms, though this would require Google to infer "git checkout" but I didn't include git because that would introduce another universe of unhelpful results.
https://dzone.com/articles/getting-started-with-jenkins-the-... was included which doesn't include "azure" at all, though this is obviously Google being cheeky.
Of course I could also call this somewhat sinister, as Google is basically saying I should ditch a direct competitor to their services and instead use a self-hosted service. Or maybe I'm projecting since I would like to ditch Azure DevOps and use Jenkins, but in any case there's an example.
Feel free to play with it: https://www.google.com/search?rlz=1C1CHBF_enUS820US820&biw=1...
Of course, in this case it was a networking problem so I do have to admit that usually when Google starts ignoring what I typed it's because the answer to the question is something else entirely. Though sometimes I know exactly what I'm asking for and Google doesn't get it.
I think possibly what is happening here is that the index believes "azure" is on the page.
Consider the second result here: https://www.google.com/search?q=%22azure%22+%22Allows+adding...
(the one that starts java.dzone.com but leads to the same article).
It appears to have captured at index time a phrase "Microservices and Serverless on Azure" that is no longer in the artcile (possibly a link to another article).
Perhaps a Googler can explain exactly what is happening.
Because anyone who's used Google in the last 10 years knows that Google tailors its results to what it thinks you want to see.
So a search query that fails for one HN reader may work for another, or at least work differently.
A repeated frustration in my life has been explaining to bosses that the search results that appear on their personal phone are not the same as what will appear on a client's computer.
Unfortunately, it is no longer possible to use Google Search for searching in Internet. You are only allowed to look up viral memes and query neural networks, trained by other people's searches. Searching for rare and unique things will quickly get you banned. An interesting side-effect: using modern Google to check if name is vacant is meaningless. I used to google for names to see, if something else used them, but Google's search repeatedly returned me 0 results, even when there were multiple pages with that particular name in title, many of them years old. Searching for the same thing couple of weeks later have suddenly returned hundreds of hits.
I wonder, how much it costs to actually query Google's database instead of some distant neural network approximation. Apparently, Google's own employees can't afford it anymore — some of them are using DuckDuckGo instead (they even added it to Chrome, lol)
And if I were to hazard a guess I think you dramatically overestimate the role of neural networks in search in general.
This happens often when creating complex search terms with 'inurl' and 'intext' operators. This happens to me at least once a month.
I suppose it sometimes looks like my account is used for botting, but then again: why wouldn't I be allowed to connect my bot to their results, given that google uses bots to index the content in the first place?
Despite the fact that I could probably adjust to better fit their 'nothing weird going on here' preconceptions, I think I'd rather complain and hope that over time it's google that will change.
Then consider yourself lucky. The post was a little rambling, but it wasn't wrong.
You get warnings and captchas.
Frequently they are unsolvable captchas that just waste your time. :(
I'd hazard a random guess that 90% of the time someone looks up a phone number for an unlisted number, they want to know if it's a scammer/spammer. So why the author seems to think this is the "wrong" result to show seems pretty strange to me.
And the algorithm in general appears to frustrate many people, if the comments here are anything to go by.
Books:
Lucene in Action http://manning.com/books/lucene-in-action Solr in Action https://www.manning.com/books/solr-in-action Relevant Search http://manning.com/books/relevant-search (disclaimer, my book) Elasticsearch Definitive Guide (free/online) https://www.elastic.co/guide/en/elasticsearch/guide/current/... Introduction to Info. Retrieval https://nlp.stanford.edu/IR-book/information-retrieval-book.... Deep Learning for Search http://manning.com/books/deep-learning-for-search
Training:
Lucidworks Training https://lucidworks.com/resources/solr-training-and-consultin... Elastic's training https://training.elastic.co/ OpenSource Connection's training (disclaimer, my company's training) http://o19s.com/events/training
Conferences:
Haystack http://haystackconf.com (disclaimer I'm a co-organizer) Activate http://activate.conf SIGIR http://sigir.org ECIR http://ecir2019.org/ Search Solutions https://irsg.bcs.org/SearchSolutions/2018/ss2018tutorials.ph... Berlin Buzzwords https://berlinbuzzwords.de/ MICES E-Commerce Search - http://mices.co
Blogs:
OpenSource Connections blog - http://o19s.com/blog (disclaimer - my companys blog) Lucidworks Blog - https://lucidworks.com/blog/ Sematext Blog - https://sematext.com/blog/ Elastic's blog http://elastic.co/blog