PageRank is an algorithm developed by 📝Larry Page and 📝Sergey Brin at 📝Stanford University in 1996 to rank web pages based on their importance within a network. The PageRank system evaluates the quantity and quality of links pointing to a webpage, interpreting each link as a vote of confidence. Pages with more inbound links from reputable sources receive higher scores, making them more likely to appear prominently in search results. The algorithm was a core component of 📝Google’s early search engine and helped distinguish it from competitors by prioritizing relevance and authority rather than relying solely on keyword density. PageRank employs a probabilistic model, often compared to the “random surfer” concept, where a hypothetical user navigates the web by clicking on links at random. This model calculates the probability distribution of landing on a given page, which determines its rank. Though still foundational, PageRank has since been supplemented by numerous other factors in modern search ranking systems.

Contexts

• 🏷️#alphabet (See: 📝Alphabet)
• 🏷️#google (See: 📝Google)