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MrMagik14 t1_iu348n1 wrote

What’s the solution!!??

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[deleted] t1_iu34owz wrote

[deleted]

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MrMagik14 t1_iu34uyq wrote

I don’t know what you are saying, but it sounds offensive! I apologize for asking.

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just-an-astronomer t1_iu395bl wrote

A transition matrix is a big table that measures how connected pages are with other pages. One of Google's co-founders, Larry Page, wrote his thesis on performing specific math on these matrices that rank how well connected they are with other things that are connected well, this method is called Page rank, not because it ranks webpages, but because Larry Page invented it.

There's not really a way to describe the specifics of how Page rank work without knowing some linear algebra. You're looking for a "solution" to the matrix called its eigenvalues and eigenvectors, which is a Linear Algebra concept I can't quite eli5

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Phrygiaddicted t1_iu440va wrote

>eigenvalues and eigenvectors, which is a Linear Algebra concept I can't quite eli5

eigenvectors are just certain vectors that when multiplied by the matrix, still point in the same direction. Aû = û.

eigenvalue is how much that vector gets stretched by. Au = eu.

so it could very crudely be summed up by saying "if you keep following links over and over, where do you likely end up"

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spider-bro t1_iu5qkk7 wrote

Google was the first search engine to associate search terms with pages by using the link text from the upstream end of a link.

Before that pages were asked to categorize themselves by adding metadata to the HTML source of the page. The title, the headings within the body, and metadata tags in the head were used to categorize for Yahoo, Alta Vista, etc. Google came along and put precedence on the link text. For example in this link: the funniest thing in existence, Google would associate that webpage with the word "funniest" in its search.

By relying on external "categorizations" that relied on the natural English that others used to describe what a link was pointing to, Google was able to tap into a distributed intelligence that associated words with web pages that more closely resembled how a searcher would think of the page.

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