Technology Overview

We stand alone in our focus on developing the "perfect search engine," defined by co-founder Larry Page as something that, "understands exactly what you mean and gives you back exactly what you want." To that end, we have persistently pursued innovation and refused to accept the limitations of existing models. As a result, we developed our serving infrastructure and breakthrough PageRank™ technology that changed the way searches are conducted.
From the beginning, our developers recognized that providing the fastest, most accurate results required a new kind of server setup. Whereas most search engines ran off a handful of large servers that often slowed under peak loads, ours employed linked PCs to quickly find each query's answer. The innovation paid off in faster response times, greater scalability and lower costs. It's an idea that others have since copied, while we have continued to refine our back-end technology to make it even more efficient.

• PageRank Technology: PageRank reflects our view of the importance of web pages by considering more than 500 million variables and 2 billion terms. Pages that we believe are important pages receive a higher PageRank and are more likely to appear at the top of the search results.
  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. We have always taken a pragmatic approach to help improve search quality and create useful products, and our technology uses the collective intelligence of the web to determine a page's importance.
• Hypertext-Matching Analysis: Our 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), our technology analyzes the full content of a page and factors in fonts, subdivisions and the precise location of each word. We also analyze the content of neighboring web pages to ensure the results returned are the most relevant to a user's query.