PageRank is an algorithm developed by Google co-founders Larry Page and Sergey Brin that measures the importance and authority of web pages based on the quality and quantity of links pointing to them. It played a significant role in Google's early success as a search engine.
Key characteristics of PageRank:
- Link-based: PageRank relies on the web's link structure to determine a page's importance. The more high-quality links a page receives, the higher its PageRank.
- Recursive: A page's PageRank is calculated based on the PageRank of the pages linking to it. This recursive nature means that a page's importance is influenced by the importance of the pages linking to it.
- Logarithmic scale: PageRank is measured on a logarithmic scale, typically ranging from 0 to 10. A page with a PageRank of 4 is considered ten times more authoritative than a page with a PageRank of 3.
- Damping factor: To prevent endless loops and rank sinks, PageRank includes a damping factor (usually 0.85) that simulates the probability of a user continuing to click on links as they browse.
- Iterative calculation: PageRank is calculated iteratively, with each iteration refining the PageRank values until they converge to a stable set of values.
- Inbound links: PageRank primarily considers the quantity and quality of inbound links (links pointing to a page) rather than outbound links (links from a page to other pages).
While PageRank was a groundbreaking algorithm in the early days of search engines, it is now just one of many factors considered in Google's more sophisticated ranking algorithms. However, the core principles of PageRank, such as the importance of high-quality links, remain influential in modern SEO.