The Google Pagerank Algorithm and How It Works

Spoiler

Memahami Kerja Google Page Rank English Version
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what is PageRank?

In short PageRank is a "vote"￾, by all the other pages on the Web, about how important a page is. A link to a page counts as a vote of support. If there's no link there's no support (but it's only an abstention from voting rather than a vote against the page). Quoting from the original Google paper, PageRank is defined like this:
We assume page A has pages T1…Tn which point to it (i.e., are citations). The parameter d is a damping factor which can be set between 0 and 1. We usually set d to 0.85. There are more details about d in the next section. Also C(A) is defined as the number of links going out of page A. The PageRank of a page A is given as follows:
PR(A) = (1-d) + d (PR(T1)/C(T1) + … + PR(Tn)/C(Tn))
Note that the PageRanks form a probability distribution over web pages, so the sum of all web pages\' PageRanks will be one.
PageRank or PR(A) can be calculated using a simple iterative algorithm, and corresponds to the principal eigenvector of the normalized link matrix of the web.
but that's not too helpful so let's break it down into sections.

1. PR(Tn) – Each page has a notion of its own self-importance. That's "PR(T1)"￾ for the first page in the web all the way up to "PR(Tn)" for the last page
2. C(Tn) – Each page spreads its vote out evenly amongst all of it's outgoing links. The count, or number, of outgoing links for page 1 is "C(T1)", "C(Tn)"￾ for page n, and so on for all pages.
3. PR(Tn)/C(Tn) – so if our page (page A) has a backlink from page "n"￾ the share of the vote page A will get is "PR(Tn)/C(Tn)"
4. d(… – All these fractions of votes are added together but, to stop the other pages having too much influence, this total vote is "damped down"￾ by multiplying it by 0.85 (the factor "d"￾)
5. (1 – d) – The (1 – d) bit at the beginning is a bit of probability math magic so the "sum of all web pages' PageRanks will be one": it adds in the bit lost by the d(…. It also means that if a page has no links to it (no backlinks) even then it will still get a small PR of 0.15 (i.e. 1 – 0.85). (Aside: the Google paper says "the sum of all pages"￾ but they mean the "the normalised sum" otherwise known as "the average" to you and me.

How is PageRank Calculated?

This is where it gets tricky. The PR of each page depends on the PR of the pages pointing to it. But we won't know what PR those pages have until the pages pointing to them have their PR calculated and so on… And when you consider that page links can form circles it seems impossible to do this calculation! But actually it's not that bad. Remember this bit of the Google paper:
PageRank or PR(A) can be calculated using a simple iterative algorithm, and corresponds to the principal eigenvector of the normalized link matrix of the web.

What that means to us is that we can just go ahead and calculate a page's PR without knowing the final value of the PR of the other pages. That seems strange but, basically, each time we run the calculation we're getting a closer estimate of the final value. So all we need to do is remember the each value we calculate and repeat the calculations lots of times until the numbers stop changing much. Lets take the simplest example network: two pages, each pointing to the other:

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Each page has one outgoing link (the outgoing count is 1, i.e. C(A) = 1 and C(B) = 1).
Guess 1

we don't know what their PR should be to begin with, so let's take a guess at 1.0 and do some calculations:
d = 0.85 PR(A) = (1 – d) + d(PR(B)/1) PR(B) = (1 – d) + d(PR(A)/1) i.e.
PR(A) = 0.15 + 0.85 * 1
= 1 PR(B) = 0.15 + 0.85 * 1
= 1 Hmm, the numbers aren't changing at all! So it looks like we started out with a lucky guess!!!
Guess 2

No, that's too easy, maybe I got it wrong (and it wouldn't be the first time). Ok, let's start the guess at 0 instead and re-calculate:
PR(A) = 0.15 + 0.85 * 0 = 0.15 PR(B) = 0.15 + 0.85 * 0.15 = 0.2775 NB. we've already calculated a "next best guess"￾ at PR(A) so we use it here And again:
PR(A) = 0.15 + 0.85 * 0.2775 = 0.385875 PR(B) = 0.15 + 0.85 * 0.385875 = 0.47799375 And again
PR(A) = 0.15 + 0.85 * 0.47799375 = 0.5562946875 PR(B) = 0.15 + 0.85 * 0.5562946875 = 0.622850484375 and so on. The numbers just keep going up. But will the numbers stop increasing when they get to 1.0? What if a calculation over-shoots and goes above 1.0?
Guess 3

Well let's see. Let's start the guess at 40 each and do a few cycles:

• PR(A) = 40 PR(B) = 40

First calculation
PR(A) = 0.15 + 0.85 * 40 = 34.15 PR(B) = 0.15 + 0.85 * 34.15 = 29.1775 And again
PR(A) = 0.15 + 0.85 * 29.1775 = 24.950875 PR(B) = 0.15 + 0.85 * 24.950875 = 21.35824375 Yup, those numbers are heading down alright! It sure looks the numbers will get to 1.0 and stop.
Here's the code used to calculate this example starting the guess at 0: Show the code | Run the program

• Principle: it doesn't matter where you start your guess, once the PageRank calculations have settled down, the "normalized probability distribution"￾ (the average PageRank for all pages) will be 1.0

Spoiler

maaf kalo salah kamar, tolong dipindah saja kalo salah Om mod sumber page dari hxxp://sirgroane.net/google-page-rank/

 

wah kok jadi mumet Om kepalaku.....
mungkin yang di bawah bisa jelasin gmn maksudnya ini....

 

mana mana sopo yang ada di bawah ?

 

Ampun nih, rudet... Tapi yang penting cari backlink berkualitas...

 

beuh, teori itu...wong google ae bingung cara nerapin pageranknya,,,jangan percaya klo lom nyoba sendiri

 

wow mantap nih , ane pelajari dulu yah , thanks bro

 

ane pelajari dulu deh,maklum otak newbie

 

mumet otak ku om. harus baca pelan2 neh supaya paham

 

buka gugel translet dulu, coz ane gak faham bahasa bule

 

Rumusku lebih simple

Good Web + Good Content = $$$

 

inti dari penjelesan Google Algolrithm itu adalah...

Spoiler

sama dengan ente.. ane juga masih bingugn

 

kyknya iya nih..
terbukti dah setengah taon lbh ga update pagerank

 

betul. teori banget itu. mau terapin malah susah. PR is hajar aja bleh...

 

wah kudu diajar bahasa inggeris heula

 

mencoba menyimak walo masih bingung mpe sekarang cara google ngasih PR ke sebuah blog / webiste.. ada blog aku yang gak dioptimasi BL nya dapet PR sementera yang dicariin BL kemana2 mentok di PR 0 terus...

 

KISS (KEEP IT SIMPLE SOB)!

 

ga ngertiiiii

rumet bgt y

 

buset dah jadi kalkulus deh...

 

indo nya aja lah

 

Plus Good Backlinks from PR10