6 ms·

The Anatomy of a Large-Scale Hypertextual Web Search Engine (1997)

38 points by dcpdx 12y ago

trg2 12y ago
Love this. The first sentence is still very telling: In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext.
gp2000 12y ago
Google of the past has severe doubts about Google of the present: ...we expect that advertising funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers.
- srcmap 12y ago
  Young Jedi felt the power of the dark side.
extofer 12y ago
I agree, the first statement was captivating. It's nostalgic and yet, a form of forecasting in it's own right, what becomes future technology in this architecture
hrish2006 12y ago
"So we are optimistic that our centralized web search engine architecture will improve in its ability to cover the pertinent text information over time and that there is a bright future for search" Wow!
- vayarajesh 12y ago
  Wow indeed!
qwerb 12y ago
Reading this is like time travel.
vayarajesh 12y ago
> "There are two versions of this paper -- a longer full version and a shorter printed version. The full version is available on the web and the conference CD-ROM" Does anyone have a link to the full version? I would love to read more in detail.. it is so inspiring I think after E=MC2 , The PageRank algorithm "PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))" is the formula which changed the entire world..
- sytelus 12y ago
  This version is actually the full version. The short version was designed for printing out/conference while longer version is designed for hosting on web. Also there is a book on the subject Google's PageRank and Beyond http://books.google.com/books?id=KsHTl_2Pfl8C http://books.google.com/books?id=KsHTl_2Pfl8C Other interesting articles: THE $25,000,000,000∗ EIGENVECTOR http://www.rose-hulman.edu/~bryan/googleFinalVersionFixed.pdf http://www.rose-hulman.edu/~bryan/googleFinalVersionFixed.pd... How Google Finds Your Needle in the Web's Haystack http://www.ams.org/samplings/feature-column/fcarc-pagerank http://www.ams.org/samplings/feature-column/fcarc-pagerank The Google Pagerank Algorithm and How It Works http://www.cs.princeton.edu/~chazelle/courses/BIB/pagerank.htm http://www.cs.princeton.edu/~chazelle/courses/BIB/pagerank.h...
  - vayarajesh 12y ago
    Thanks!
bulte-rs 12y ago
I remember citing this article in my thesis and thinking "damn has it been 10 years already". I was 23 back then. :| Thinking of the PageRank algorithm as a eigenvalue problem was one of the few 'things' that were a real eye opener for me and allowed me to actually connect maths and computer science for these practical purposes.

38 points by dcpdx 12y ago

trg2 12y ago

Love this. The first sentence is still very telling: In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext.

gp2000 12y ago

Google of the past has severe doubts about Google of the present: ...we expect that advertising funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers.

srcmap 12y ago
Young Jedi felt the power of the dark side.

extofer 12y ago

I agree, the first statement was captivating. It's nostalgic and yet, a form of forecasting in it's own right, what becomes future technology in this architecture

hrish2006 12y ago

"So we are optimistic that our centralized web search engine architecture will improve in its ability to cover the pertinent text information over time and that there is a bright future for search" Wow!

vayarajesh 12y ago
Wow indeed!

qwerb 12y ago

Reading this is like time travel.

vayarajesh 12y ago

> "There are two versions of this paper -- a longer full version and a shorter printed version. The full version is available on the web and the conference CD-ROM" Does anyone have a link to the full version? I would love to read more in detail.. it is so inspiring I think after E=MC2 , The PageRank algorithm "PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))" is the formula which changed the entire world..

sytelus 12y ago
This version is actually the full version. The short version was designed for printing out/conference while longer version is designed for hosting on web. Also there is a book on the subject Google's PageRank and Beyond http://books.google.com/books?id=KsHTl_2Pfl8C http://books.google.com/books?id=KsHTl_2Pfl8C Other interesting articles: THE $25,000,000,000∗ EIGENVECTOR http://www.rose-hulman.edu/~bryan/googleFinalVersionFixed.pdf http://www.rose-hulman.edu/~bryan/googleFinalVersionFixed.pd... How Google Finds Your Needle in the Web's Haystack http://www.ams.org/samplings/feature-column/fcarc-pagerank http://www.ams.org/samplings/feature-column/fcarc-pagerank The Google Pagerank Algorithm and How It Works http://www.cs.princeton.edu/~chazelle/courses/BIB/pagerank.htm http://www.cs.princeton.edu/~chazelle/courses/BIB/pagerank.h...
- vayarajesh 12y ago
  Thanks!

bulte-rs 12y ago

I remember citing this article in my thesis and thinking "damn has it been 10 years already". I was 23 back then. :| Thinking of the PageRank algorithm as a eigenvalue problem was one of the few 'things' that were a real eye opener for me and allowed me to actually connect maths and computer science for these practical purposes.