Google (GOOG)

The Technology Behind Search and Our User Products and Services

Our web search technology uses a combination of techniques to determine the importance of a web page independent of a particular search query and to determine the relevance of that page to a particular search query.

Ranking Technology. One element of our technology for ranking web pages is called PageRank. While we developed much of our ranking technology after Google was formed, PageRank was developed at Stanford University with the involvement of our founders and was therefore published as research. PageRank is a query-independent technique for determining the importance of web pages by looking at the link structure of the web. PageRank treats a link from web page A to web page B as a “vote” by page A in favor of page B. The PageRank of a page is the sum of the pages that link to it. The PageRank of a web page also depends on the importance (or PageRank) of the other web pages casting the votes. Votes cast by important web pages with high PageRank weigh more heavily and are more influential in deciding the PageRank of pages on the web.

Text-Matching Techniques. Our technology employs text-matching techniques that compare search queries with the content of web pages to help determine relevance. Our text-based scoring techniques do far more than count the number of times a search term appears on a web page. For example, our technology determines the proximity of individual search terms to each other on a given web page, and prioritizes results that have the search terms near each other. Many other aspects of a page’s content are factored into the equation, as is the content of pages that link to the page in question. By combining query independent measures such as PageRank with our text-matching techniques, we are able to deliver search results that are relevant to what people are trying to find.

Infrastructure. We provide our products and services using our homegrown software and hardware infrastructure, which provides substantial computing resources at low cost. We currently use a combination of off-the-shelf and custom software running on clusters of commodity computers. Our considerable investment in developing this infrastructure has produced several benefits. This infrastructure simplifies the storage and processing of large amounts of data, eases the deployment and operation of large-scale global products and services, and automates much of the administration of large-scale clusters of computers. Although most of this infrastructure is not directly visible to our users, we believe it is important for providing a high-quality user experience. It enables significant improvements in the relevance of our search and advertising results by allowing us to apply superior search and retrieval algorithms that are computationally intensive. We believe the infrastructure also shortens our product development cycle and lets us pursue innovation more cost effectively.

The Technology Behind Search and Our User Products and Services

The Technology Behind Search and Our User Products and Services

Our web search technology uses a combination of techniques to determine the importance of a web page independent of a particular search query and to determine the relevance of that page to a particular search query.

Ranking Technology. One element of our technology for ranking web pages is called PageRank. While we developed much of our ranking technology after Google was formed, PageRank was developed at Stanford University with the involvement of our founders and was therefore published as research. PageRank is a query-independent technique for determining the importance of web pages by looking at the link structure of the web. PageRank treats a link from web page A to web page B as a “vote” by page A in favor of page B. The PageRank of a page is the sum of the pages that link to it. The PageRank of a web page also depends on the importance (or PageRank) of the other web pages casting the votes. Votes cast by important web pages with high PageRank weigh more heavily and are more influential in deciding the PageRank of pages on the web.

Text-Matching Techniques. Our technology employs text-matching techniques that compare search queries with the content of web pages to help determine relevance. Our text-based scoring techniques do far more than count the number of times a search term appears on a web page. For example, our technology determines the proximity of individual search terms to each other on a given web page, and prioritizes results that have the search terms near each other. Many other aspects of a page’s content are factored into the equation, as is the content of pages that link to the page in question. By combining query independent measures such as PageRank with our text-matching techniques, we are able to deliver search results that are relevant to what people are trying to find.

In addition, we provide our products and services using our homegrown software and hardware infrastructure, which provides substantial computing resources at low cost. We currently use a combination of off-the-shelf and custom software running on clusters of commodity computers. Our considerable investment in developing this infrastructure has produced several benefits. This infrastructure simplifies the storage and processing of large amounts of data, eases the deployment and operation of large-scale global products and services, and automates much of the administration of large-scale clusters of computers. Although most of this infrastructure is not directly visible to our users, we believe it is important for providing a high-quality user experience. It enables significant improvements in the relevance of our search and advertising results by allowing us to apply superior search and retrieval algorithms that are computationally intensive. We believe the infrastructure also shortens our product development cycle and lets us pursue innovation more cost effectively.