PageRank

PageRank is a link analysis algorithm used by Google to assign a numerical weight to each web page, reflecting its relative importance within a network of hyperlinks. It treats the web as a directed graph where pages are nodes and links are edges; a page is considered more important if it is linked to by other important pages. In effect, PageRank estimates the probability that a random web surfer lands on a given page.

Developed at Stanford University by Larry Page and Sergey Brin in 1996–1998, PageRank was described in The PageRank Citation Ranking: Bringing Order to the Web (1998) and became a core component of Google's early search system.

Algorithmically, PageRank uses a Markov chain model with a damping factor d (commonly around 0.85). The rank is computed by iterating the Google matrix until convergence, with a teleportation step allowing jumps to random pages to ensure stability; sink nodes are handled by distributing their rank accordingly.

Today PageRank is one of many signals used to rank search results. It is not a sole measure of quality or relevance, and public exposure to exact weights has diminished as more proprietary signals are added and link manipulation techniques have evolved.