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Show HN: Didyougogo – An Altavista slayer

didyougogo.com

51–60 of 131 posts

Re: Show HN: Didyougogo – An Altavista slayer

#51
post #44

Earlier quoted context omitted.

Thanks! 1. You may submit a page. When I have a little more capacity that just 1 CPU/1 GB RAM I will also crawl. 2. I'll look into it. Thank you.

Would the common crawl dataset be useful to you starting out? http://commoncrawl.org

Yes absolutely. I have been holding off crawling because I have no server capacity yet. That will probably sort itself out pretty soon from the looks of it. When I have the disk space I'll start using their data.

Re: Show HN: Didyougogo – An Altavista slayer

#52
post #34

Interesting idea. Isn't it a little late to slay Alta Vista though? :) I searched for apple. Top result was the archive.org macos that showed up here on HN recently, 2nd and 3rd were apple.com indexed 10s apart. Then some odd results - though they do include the word apple on page just once. The imdb page for 12 Monkeys appears 3 times. I guess you're not trimming duplicates? Seems like you need some way to weight ra…

I "googled" Google using Did yougogo, and Google.com didn't appear once on the first page. Funny.

If you submit Google to the "gogo" index it should start to appear when you query.

Did you submit both a query and a URL?

Did you go go?

http://didyougogo.com/add

Re: Show HN: Didyougogo – An Altavista slayer

#55
post #35

when i submit something to the search engine, it produces a result that doesn't have anything to do with the search term. it's unclear to me how i am supposed to help improve this.

I'll make sure the right people understand how to fix things like that ASAP because I love that you got the feeling you wanted to fix it.

There is something wrong currently with relevance, probably because of query parsing errors but perhaps also in how text is tokenized. This whole idea revolves around relevance so this is of course embarrassing. But it's 0.1 alpha. And it _did_ work on my machine.

Thanks for trying.

Re: Show HN: Didyougogo – An Altavista slayer

#56
post #46

Earlier quoted context omitted.

Major search engines test every release against a list of search queries. You could start with https://trends.google.com/trends/topcharts . You should have an automated test script with a list of (query, good URL) pairs and make sure the good URL appears in the top few results.

As preparation for this demo, yes I absolutely should have run such a test. Eagerness won. Thanks for the link.

Not just for demos, but to help you hack. You can make a small change to the algorithm and re-run the test and see if the score goes up or down. It's very convenient for testing changes deep inside the code.

Re: Show HN: Didyougogo – An Altavista slayer

#57
The index is super tiny. A search for "the" got 112 results. Seems like a quick way to explore the entire index. Also it indexes pages twice if you submit them twice, so that needs to be fixed.

But for some crazy reason, I kinda like this. It feels like the 90s internet. The links included so far have that same random mix of lots of nerdy links, homepages & personal blogs, a few religious sites, and the occasional big news website. Because there's no crawler yet, it's limited to the specific pages people thought were noteworthy. And because the index is so limited, I'm stumbling on interesting things.

It's so weird looking at this and thinking "Y'know, maybe this could also work if the links were curated into yet another hierarchical officious oracle", or "if this site let me pay to show a small text ad on the side when someone searched for a relevant keyword, I might spend a few dollars here".

Someone submitted the "Strawberry Pop-Tart Blow-Torches" page, which is one of my earliest internet memories. Whoever submitted that, thank you for the nostalgia!

Re: Show HN: Didyougogo – An Altavista slayer

#58
post #13

Sounds too good to be true. What's the catch?

The catch is: this is 0.1 alpha software. I need a small team and some server capacity to get rolling. I need people to submit URLs. And a few hundred queries per second. That would scare the living shit out of big league search engines and might wake up some investor wanting to throw money at this.

In addition to users submitting articles, is there a reason this doesn't have a spider of its own based off something like the Google zeitgeist to seed some topics?

This project looks neat, I think first experiences with it would be much more improved if you could seed it with some content.

Maybe this could run my search with other search engines to compare and gain insights.

Re: Show HN: Didyougogo – An Altavista slayer

#59
post #6

Is this supposed to be a joke? I can't tell. The index is certainly extremely limited.

The challenge is not building the search engine, it’s in building the index. That’s why google wants every drop of data

I've sometimes wondered whether it would work for a search engine to reduce the indexing problem by focusing more on quality than quantity. Rather than indexing everything in the universe and then trying to rank it, focus on maximizing ROI and keeping the aggregate quality of the corpus up by aggressively pruning low-quality paths up-front. In practice this might require splitting the difference between classic Yahoo and modern search engines, with manual maintenance of various black/white/greylists and rules to assign different quality metrics for different users on social media sites, which might reduce the effectiveness of this approach. Anyone know if something like this has been tried?

Re: Show HN: Didyougogo – An Altavista slayer

#60
I'm Marcus, founder of Didyougogo and author of the software behind it. For the past ten years I've been trying to improve my programming and math skills to get to a level where I could write a proper web search engine for the written word using absolute cutting-edge IR methods. The final result is something I have not seen or read about: a language represented as a 65K wide vector-space, serialized into a binary tree that is balanced according to node's cosine angle between them and their closest neighbours. Querying is very fast, even for long phrases. Fuzzy, prefix, suffix and wildcard type queries comes for free with the vector-space model. The system uses relatively little resources and can run on as little as 1 CPU and 1GB RAM.

Is there any further technical documentation than this (besides the source code)?

I tried searching some of the terms in this description on Google, but found little specific information. One search turned up k-d trees. Is this related?

https://en.wikipedia.org/wiki/K-d_tree

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