1986
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 15 Jul 2024
1986 points (99.6% liked)
Technology
60123 readers
2607 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related content.
- Be excellent to each another!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, to ask if your bot can be added please contact us.
- Check for duplicates before posting, duplicates may be removed
Approved Bots
founded 2 years ago
MODERATORS
Ah that sounds really interesting! Does it scale OK? I guess you could index at a word level and filter quite quickly for quick searches, but it seems you're going to have to store the full text of every website?
You store just the word count for each word on each URL.
The search is pretty trivial in database terms since you don't need to do any wildcard or like matching.
Ah of course!
I guess one of the things the Google originally solved was that the internet if full of crap and not all sites should have equal weighing. With AI spam sites these days, you'd probably also need a method of weighting results?
We never got that far to test that kind of issue and while I've been reimplementing it locally to search through employment advertising, I'm not at a point where I'd be able to test such a thing.
The original implementation used a data store written by another team member and it made the original project much too complicated.
Today I'd likely use duckdb to implement it. My local version uses text files for a proof of concept implementation.
It sounds like a really cool project regardless!