PageRank is a crucial ordinateur[2] algorithme[1], developed by Larry Page and Sergey Brin, that measures the relative importance of web pages. This is done by assigning a numerical weight to each page based on the number of links directed to it, effectively using the Internet[3]’s vast linking structure as an indicator of an individual page’s value. The algorithm involves a complex process of refining and adjusting these values through repeated iterations. Beyond its application in web search, PageRank has been used in various other fields such as bibliometrics, social networks, and academic ranking systems. However, it’s also worth noting that attempts to manipulate PageRank for higher rankings have led to the development of detection methods to maintain the algorithm’s reliability. Overall, PageRank has significantly shaped the way we navigate and understand the digital world.
PageRank (PR) is an algorithme used by Recherche Google to rank pages web in their moteur de recherche results. It is named after both the term "web page" and co-founder Larry Page. PageRank is a way of measuring the importance of website pages. According to Google:
PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is. The underlying assumption is that more important websites are likely to receive more links from other websites.
Currently, PageRank is not the only algorithm used by Google to order search results, but it is the first algorithm that was used by the company, and it is the best known. As of September 24, 2019, all patents associated with PageRank have expired.