Published on February 28, 2014
Presented By.. Rishabh Dev Singh
Contents.. • Uncover the secrets of Google. • How it all works. • Understanding the technology „PAGE RANK‟ behind it. • Why „PAGE RANK „ is a pioneering technology. • Reference.
Why is Google Different ??
Step1… • Exploring the web…
Crawling… • Special Software known as “Googlebot” is used. • Runs on large number of computers to crawl the web. • Googlebot starts from its last crawl status and busily looks for new sites,change to current and invalid links.
Step 2… • Organizing the data.. • Report on the pages visited & thus index is updated. • Index like something at back of the book.
Step3… • Presenting the Data.. • Google search doesn‟t just drive into index & fish around for what it needs. • Use of Knowledge Graph. • Several factors are used to present the most relevant search results.
Factors… Some of the know factors.. • Type of content. • Quality of content. • Freshness of content. • The user‟s region. • Legitimacy of the site. • Name and address of the website. • Search word synonyms. • Social media promotions. • How many links point to a particular web page. • The value of those links.
Page Rank… • Developed by Larry Page and Sergey Brin in 1998 • Trademark of Google • Patented by Stanford Unvirsity • Back bone of Google Search Technology
UNDERSTANDING PAGE RANK
Page Rank Technology.. • Rank pages based on the number of other pages that link to it. • Gives an indication of the relative importance of a page. • Hence,an appropriate „SERP‟(Search Engine Result Page) listing. • Calculated by nature and number of „ back links „
Definition of Page Rank.. • “We assume page A has pages T1…Tn which point to it.The parameter „d‟ is a damping factor which can be set between 0 & 1. We usually set „d‟ to 0.85.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 Page Ranks form a probability distribution over web pages , so the sum of all web pages , Page Ranks will be one”
Calculating Page Rank...
Definition Of Terms • PR: Shorthand for PageRank: the actual , real ,page rank for each page as calculated by Google. • Back link : If page A links out to page B , the page B is said to have a „ back link‟ from page A.
PR(A) =(1-d)+d(PR(T1)/C(T1)+..+PR(Tn)/C(Tn)) • The PR of each page depends on the PR of the pages pointing to it. • We won‟t know what PR those pages have until the pages pointing to them have their PR calculated. • ………….and so on..
Seems impossible to do this calculation….
BUT THERE IS A SOLUTION
• Page Rank can be calculated using simple iterative algorithms . • What we need to do .. • *Remember the each value we calculate. • *Repeat the calculations lots of times.
How Many Times ???
Until the number stop changing much…
Page A Page B • Let ,us assume that PR =1.0 & d=0.85 PR(A) = (1-d) + d(PR(B)/1) PR(B) =(1-d)+d(PR(A)/1) On calculation.. PR(A) = 0.15+0.85*1 =1 PR(B) = 0.15 + 0.85*1=1
OK BUT WHY SHOULD I ASSUME PR =1 ? WHAT IF NOT…
So , Lets start with PR=0 • PR(A) =0.15 +0.85 *0=0.15 • PR(B)=0.15 + 0.85*0.15=0.2775 • 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 Inference : PR approaches 1.. •
Example… • Let us assume :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 • ………PR will approach and settle down @1
• The home page has got the highest PR…after all it is the one getting most numbers of incoming.. • But what's happened to the average ? It‟s only 0.378 !!!
Lets, take a look at the “external site “ pagesWhat’s happening to their Page Rank ?
• That‟s better- It does work after all !! • And look at the PR of our home page !! • All those incoming links sure make a difference
Regardless the number of pages, average PR will always be 1.0 at best. And that’s how you searching happens on GOOGLE.
References… • Sergey Brin & Larry Page , “Anatomy of Large-Scale Hyper textual Web Search Engine” • http://www.cs.princeton.edu/~chazelle/courses/BIB /pagerank.htm • http://en.wikipedia.org/wiki/PageRank • http://www.whitelines.nl/html/google-pagerank.html • http://www.google.co.in/insidesearch/howsearchw orks/thestory/
Presentación que realice en el Evento Nacional de Gobierno Abierto, realizado los ...
In this presentation we will describe our experience developing with a highly dyna...
Presentation to the LITA Forum 7th November 2014 Albuquerque, NM
Un recorrido por los cambios que nos generará el wearabletech en el futuro
Um paralelo entre as novidades & mercado em Wearable Computing e Tecnologias Assis...
How Google Works. The rules for success in the Internet Century. A new book by Eric Schmidt & Jonathan Rosenberg, with Alan Eagle
For Google tips, tricks, & how Google works, visit Google Guide at www.GoogleGuide.com. Google Guide is neither affiliated with nor endorsed by ...
Google navigates the web by crawling. That means we follow links from page to page.
Hier sollte eine Beschreibung angezeigt werden, diese Seite lässt dies jedoch nicht zu.
Rated 4.4/5: Buy How Google Works by Eric Schmidt, Jonathan Rosenberg: ISBN: 9781455582341 : Amazon.com 1 day delivery for Prime members
The following infographic was created years ago when Google had a content-first focus on search. In the years since then, the rise of mobile devices has ...
Der Titel dieses Buches – „How Google works“ – ist vielversprechend, aber völlig untertrieben. Denn eigentlich prangt über Eric Schmidts dieser ...
How Search Works Search. It happens billions of times a day in the blink of an eye. Explore the art and science that makes it possible.
http://www.google.com/howgoogleworks ... How Search Works ... How Google Apps Work - Duration: ...