My name is Josef Cullhed. I am the programmer of alexandria.org and one of two founders. We want to build an open source and non profit search engine and right now we are developing in our spare time and are funding the servers ourselves. We are indexing commoncrawl and the search engine is in a really early stage.
We would be super happy to find more developers who want to help us.
Yes our documentation is probably pretty confusing. It works like this, the base score for all URLs to a specific domain is the harmonic centrality (hc). Then we have two indexes, one with URLs and one with links (we index the link text). Then we first make a search on the links, then on the URLs. We then update the score of the urls based on the links with this formula: domain_score = expm1(5 * link.m_score) + 0.1; url_score = expm1(10 * link.m_score) + 0.1;
then we add the domain and url score to url.m_score
where link.m_score is the HC of the source domain.
I'd consider contributing. Seems you have something here.
It takes us a couple of days to build the index but we have been coding this for about 1 year.
All the indexes are on disk.
Love it. Makes for a cheaper infrastructure, since SSD is cheaper than RAM.
>> It takes us a couple of days to build the index
It's hard for me to see how that could be done much faster unless you find a way to parallelize the process, which in itself is a terrifyingly hard problem.
I haven't read your code yet, obviously, but could you give us a hint as to what kind of data structure you use for indexing? According to you, what kind of data structure allows for the fastest indexing and how do you represent it on disk so that you can read your on-disk index in a forward-only mode or "as fast as possible"?
>> It's hard for me to see how that could be done much faster unless you find a way to parallelize the process
We actually parallelize the process. We do it by separating the URLs to three different servers and indexing them separately. Then we just make the searches on all three servers and merges the result URLs.
>> I haven't read your code yet, obviously, but could you give us a hint as to what kind of data structure you use for indexing?
It is not very complicated, we use hashes a lot to simplify things. The index is basically a really large hash table with the word_hash -> [list of url hashes] Then if you search for "The lazy fox" we just take the intersection between the three lists of url hashes to get all the urls which have all words in them. This is the basic idea that is implemented right now but we will of course try to improve.
details are here: https://github.com/alexandria-org/alexandria/blob/main/src/i...
I actually don't know what roaring bitmaps are, please enlighten me :)
There are some algorithms that have been optimized for intersect, union, remove (OR, AND, NOT) that work extremely well for sorted lists but the problem is usually: how to efficiently sort the lists that you wish to perform boolean operations on, so that you can then apply the roaring bitmap algorithms on them.
1. Do you have any plans to support the parsing of any additional metadata (e.g. semantic HTML, microformats, schema.org structured data, open graph, dublin core, etc)?
2. How do you plan to address duplicate content? Engines like Google and Bing filter out pages containing the same content, which is welcome due to the amount of syndication that occurs online. `rel="canonical"` is a start, but it alone is not enough.
3. With the ranking algorithm being open-source, is there a plan to address SEO spam that takes advantage of Alexandria's ranking algo? I know this was an issue for Gigablast, which is why some parts of the repo fell out of sync with the live engine.
4. What are some of your favorite search engines? Have you considered collaboration with any?
1. Yes, any structured data could definitely help improve the results, I personally like the Wikidata dataset. It's just a matter of time and resources :)
2. The first step will probably be to handle this in our "post processing". We query several servers when doing a search and often get many more results than we need and in this step we could quite easily remove identical results.
3. The ranking is currently heavily based on links (same as Google) so we will have similar issues. But hopefully we will find some ways to better determine what sites are actually trustworthy, perhaps with more manually verified sites if enough people would want to contribute.
4. I think that Gigablast and Marginalia Search are really cool and interesting to see how much can be done with a very small team.
Which syntaxes and vocabularies do you prefer? microformats, as well as schema.org vocabs represented Microdata or JSON-LD, seem to be the most common acc to the latest Web Data Commons Extraction Report[0]. The report is also powered by the Common Crawl.
[0]: http://webdatacommons.org/structureddata/2021-12/stats/stats...
Apologies if I missed it (and solely out of curiosity), but how roughly much does hosting Alexandria Search cost (per month)? (I'm assuming you've optimized for cost to avoid spending your own money!)
I have some other questions (around crawlers, parsing, and dependencies), but I need to read the other comments first (to see if my questions have already been answered).
The active index is running on 4 servers and we have one server for hosting the frontend and the api (the API is what is used by the frontend, ex: https://api.alexandria.org/?q=hacker%20news)
Then we have one fileserver storing raw data to be indexed. The cost for those 6 servers are around 520 USD per month.
Does this mean we’re not in Commoncrawl? Or are there any factors you weight much more heavily than Google might?
We hope we can become a useful search engine powered by open source and donations instead of ads.
1. How do you plan to finance?
2. How will you avoid SEO?
3. What kind of help would be most welcome?
1. We would prefer to be funded with donations like Wikipedia.
2. I don't think we can avoid it completely, perhaps with volunteers helping us determine the trustworthiness of websites. Do you have any suggestions?
3. I think programmers and people with experience raising money for nonprofits could help the most right now. But if you see some other way you would want to contribute, please let us know!