Been looking into a lot of the workings of Google and their advertising wing this morning, so I thought sharing some of that information might be useful…
The software behind Google’s search technology conducts a series of simultaneous calculations requiring only a fraction of a second. Traditional search engines rely heavily on how often a word appears on a web page. Google uses PageRankâ„¢ to examine the entire link structure of the web and determine which pages are most important. It then conducts hypertext-matching analysis to determine which pages are relevant to the specific search being conducted. By combining overall importance and query-specific relevance, Google is able to put the most relevant and reliable results first.
PageRank Technology: PageRank performs an objective measurement of the importance of web pages by solving an equation of more than 500 million variables and 2 billion terms. Instead of counting direct links, PageRank interprets a link from Page A to Page B as a vote for Page B by Page A. PageRank then assesses a page’s importance by the number of votes it receives.
PageRank also considers the importance of each page that casts a vote, as votes from some pages are considered to have greater value, thus giving the linked page greater value. Important pages receive a higher PageRank and appear at the top of the search results. Google’s technology uses the collective intelligence of the web to determine a page’s importance. There is no human involvement or manipulation of results, which is why users have come to trust Google as a source of objective information untainted by paid placement.
Hypertext-Matching Analysis: Google’s search engine also analyzes page content. However, instead of simply scanning for page-based text (which can be manipulated by site publishers through meta-tags), Google’s technology analyzes the full content of a page and factors in fonts, subdivisions and the precise location of each word. Google also analyses the content of neighboring web pages to ensure the results returned are the most relevant to a user’s query.
Fun reading, eh?