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Organic
- Search
Engines
Google was started
by two PhD students at Stanford University, Sergey Brin and Larry Page,
and brought a new concept to evaluating web pages. This concept, called
PageRank, has been important to the Google algorithm from the start.
PageRank relies heavily on incoming links and uses the logic that each
link to a page is a vote for that page's value. The more incoming links
a page had the more "worthy" it is. The value of each incoming link
itself varies directly based on the PageRank of the page it comes from
and inversely on the number of outgoing links on that page.
With help from PageRank, Google proved to be very good at serving
relevant results. Google became the most popular and successful search
engine. Because PageRank measured an off-site factor, Google felt it
would be more difficult to manipulate than on-page factors.
However, webmasters had already developed link-manipulation tools and
schemes to influence the Inktomi search engine. These methods proved to
be equally applicable to Google's algorithm. Many sites focused on
exchanging, buying, and selling links on a massive scale. PageRank's
reliance on the link as a vote of confidence in a page's value was
undermined as many webmasters sought to garner links purely to
influence Google into sending them more traffic, irrespective of
whether the link was useful to human site visitors.
Further complicating the situation, the default search-bracket was
still to scan an entire webpage for so-called related search-words, and
a webpage containing a dictionary-type listing would still match almost
all searches (except special names) at an even higher priority given by
link-rank. Dictionary pages and link schemes could severely skew search
results.
It was time for Google -- and other search engines -- to look at a
wider range of off-site factors. There were other reasons to develop
more intelligent algorithms. The Internet was reaching a vast
population of non-technical users who were often unable to use advanced
querying techniques to reach the information they were seeking and the
sheer volume and complexity of the indexed data was vastly different
from that of the early days. Search engines had to develop predictive,
semantic, linguistic and heuristic algorithms. Around the same time as
the work that led to Google, IBM had begun work on the Clever Project ,
and Jon Kleinberg was developing the HITS algorithm.
A proxy for the PageRank metric is still displayed in the Google
Toolbar, but PageRank is only one of more than 100 factors that Google
considers in ranking pages.
Today, most search engines keep their methods and ranking algorithms
secret, to compete for finding the most valuable search-results and to
deter spampages from clogging those results. A search engine may use
hundreds of factors in ranking the listings on its SERPs; the factors
themselves and the weight each carries may change continually.
Algorithms can differ widely: a webpage that ranks #1 in a particular
search engine could rank #200 in another search engine.
The following factors are speculation on some of the considerations
search engines may presently be using or which could be built into
their algorithms. A number of these are taken from one of Google's
patent applications , and may give some indication as to what is in the
pipeline. Some are pure speculation. It's also good to keep in mind
that Google has over 180 patents and patent applications assigned to
them at the US Patent and Trademark Office (USPTO), and a number of
those include possible insights into other factors, and other
directions that the search engine may follow, some of which may not be
consistent with this list.
Age of site
Length of time domain has been registered
Age of content
Frequency of content: regularity with which new content is added
Text size: number of words above 200-250 (not affecting Google in 2005)
Age of link and reputation of linking site
Standard on-site factors
Uniqueness of content
Related terms used in content (the terms the search engine associates
as being related to the main content of the page)
Google Pagerank (Only used in Google's algorithm)
External links, the anchor text in those external links and in the
sites/pages containing those links
Citations and research sources (indicating the content is of research
quality)
Stem-related terms in the search engine's database (finance/financing)
Incoming backlinks and anchor text of incoming backlinks
Negative scoring for some incoming backlinks (perhaps those coming from
low value pages, reciprocated backlinks, etc.)
Rate of acquisition of backlinks: too many too fast could indicate
"unnatural" link buying activity
Text surrounding outward links and incoming backlinks. A link following
the words "Sponsored Links" could be ignored
Use of "rel=nofollow" to suggest that the search engine should ignore
the link
Depth of document in site
Metrics collected from other sources, such as monitoring how frequently
users hit the back button when SERPs send them to a particular page
Metrics collected from sources like the Google Toolbar, Google
AdWords/Adsense programs, etc.
Metrics collected in data-sharing arrangements with third parties (like
providers of statistical programs used to monitor site traffic)
Rate of removal of incoming links to the site
Use of sub-domains, use of keywords in sub-domains and volume of
content on sub-domains… and negative scoring for such activity
Semantic connections of hosted documents
Rate of document addition or change
IP of hosting service and the number/quality of other sites hosted on
that IP
Other affiliations of linking site with the linked site (do they share
an IP? have a common postal address on the "contact us" page?)
Technical matters like use of 301 to redirect moved pages, showing a
404 server header rather than a 200 server header for pages that don't
exist, proper use of robots.txt
Hosting uptime
Whether the site serves different content to different categories of
users (cloaking)
Broken outgoing links not rectified promptly
Unsafe or illegal content
Quality of HTML coding, presence of coding errors
Actual click through rates observed by the search engines for listings
displayed on their SERPs
Hand ranking by humans of the most frequently accessed SERPs
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