• Dave@lemmy.nz
    link
    fedilink
    English
    arrow-up
    1
    ·
    5 months ago

    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?

    • Onno (VK6FLAB)@lemmy.radio
      link
      fedilink
      English
      arrow-up
      2
      ·
      5 months ago

      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.

      • Dave@lemmy.nz
        link
        fedilink
        English
        arrow-up
        1
        ·
        5 months ago

        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?

        • Onno (VK6FLAB)@lemmy.radio
          link
          fedilink
          English
          arrow-up
          2
          ·
          5 months ago

          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.