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PageRank algorithm for graph databases

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Re: PageRank algorithm for graph databases

#32
post #24

Earlier quoted context omitted.

There are known link structure metrics besides PageRank that both scale better and are harder to game, though I'm not sure how their effectiveness in ranking compares to PageRank in the un-gamed case. I used to work on Google web search indexing, almost 20 years ago, and (1) it has been public knowledge since around the time I left that PageRank was just one of a plethora of ranking signals going into the Learn To Ra…

>There are known link structure metrics besides PageRank that both scale better and are harder to game Any examples?

Did you see the news that has been published today about Yandex? Maybe there is something that could be interesting to you https://searchengineland.com/yandex-search-ranking-factors-l...

Re: PageRank algorithm for graph databases

#33
post #24

Earlier quoted context omitted.

There are known link structure metrics besides PageRank that both scale better and are harder to game, though I'm not sure how their effectiveness in ranking compares to PageRank in the un-gamed case. I used to work on Google web search indexing, almost 20 years ago, and (1) it has been public knowledge since around the time I left that PageRank was just one of a plethora of ranking signals going into the Learn To Ra…

>There are known link structure metrics besides PageRank that both scale better and are harder to game Any examples?

For one, the TrustRank paper discusses some variations on link structure ranking, some of which are less computationally intensive than PageRank for incrementally updating. Back 20 years ago, Google News and the more frequently updated web pages would have an incremental estimated PageRank patched in for updates that came faster than PageRank was re-calculated.

https://en.wikipedia.org/wiki/TrustRank

Re: PageRank algorithm for graph databases

#34
post #33

Earlier quoted context omitted.

>There are known link structure metrics besides PageRank that both scale better and are harder to game Any examples?

For one, the TrustRank paper discusses some variations on link structure ranking, some of which are less computationally intensive than PageRank for incrementally updating. Back 20 years ago, Google News and the more frequently updated web pages would have an incremental estimated PageRank patched in for updates that came faster than PageRank was re-calculated. https://en.wikipedia.org/wiki/TrustRank

Thanks, this is new to me.

paper link:

http://ilpubs.stanford.edu:8090/770/1/2004-52.pdf

Re: PageRank algorithm for graph databases

#35
post #5

BTW, is there a good "graph layer" for SQLite? I understand that graph databases use specific data structures to optimize for graph queries instead of row-oriented but sometimes you need something in the middle: representing graphs and doing basic queries.

I'm interested in this too. My hunch is that SQLite would be a particularly good fit for a whole bunch of queries thanks to this characteristic: https://www.sqlite.org/np1queryprob.html - "Many Small Queries Are Efficient In SQLite"

An algorithm that traverses a graph by performing hundreds of individual SELECT queries to follow a path should work much better against SQLite than against most other relational databases, due to the lack of network overhead in making each of those queries.

Re: PageRank algorithm for graph databases

#36
post #35
post #5

BTW, is there a good "graph layer" for SQLite? I understand that graph databases use specific data structures to optimize for graph queries instead of row-oriented but sometimes you need something in the middle: representing graphs and doing basic queries.

I'm interested in this too. My hunch is that SQLite would be a particularly good fit for a whole bunch of queries thanks to this characteristic: https://www.sqlite.org/np1queryprob.html - "Many Small Queries Are Efficient In SQLite" An algorithm that traverses a graph by performing hundreds of individual SELECT queries to follow a path should work much better against SQLite than against most other relational database…

This should make it a lot better: https://github.com/abetlen/sqlite3-bfsvtab-ext

Re: PageRank algorithm for graph databases

#37
post #5

BTW, is there a good "graph layer" for SQLite? I understand that graph databases use specific data structures to optimize for graph queries instead of row-oriented but sometimes you need something in the middle: representing graphs and doing basic queries.

echoing _frkl: yes, kuzu aims to fill exactly this space. an easy to use dbms that gives you the ability to model your records as a graph, do common querying and transformations, and extractions all in a high-level graph-specific query language. we are very new and have quite a lot to go but it still implements many cypher clauses, so many things can still be done.

Re: PageRank algorithm for graph databases

#38
post #23

Earlier quoted context omitted.

The PageRank algorithm can be used for so much more than... well... page ranking :) hence the article :)

Yes, it would have been nice if the article looked into ways in which the algorithm could be gamed, for the proposed applications.

With the web the SEO practitioner can affect the inputs to the model and spend money to do so.

With the other examples I am not sure they can get an advantage by gaming it. In addition the pangrank models and how they weight it are more secret than Google. Google’s algorithm is secret but leaky (the search results are public)

Re: PageRank algorithm for graph databases

#39
post #5

BTW, is there a good "graph layer" for SQLite? I understand that graph databases use specific data structures to optimize for graph queries instead of row-oriented but sometimes you need something in the middle: representing graphs and doing basic queries.

Sounds like EdgeDB [0] might be of interest to you [0] https://www.edgedb.com

> "That said, EdgeDB is built on top of Postgres."

Re: PageRank algorithm for graph databases

#40
post #5

BTW, is there a good "graph layer" for SQLite? I understand that graph databases use specific data structures to optimize for graph queries instead of row-oriented but sometimes you need something in the middle: representing graphs and doing basic queries.

Sounds like EdgeDB [0] might be of interest to you [0] https://www.edgedb.com

That made my day, thanks for sharing it
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