Linked from

The 21 pages that link to PageRank, each with the reason it gives.

• Graph theoryRelated: It applies graph structure to estimate the relative importance of web pages.

• EigenvalueRelated: Its rankings arise from an eigenvector of a modified web-link matrix.

• AlgorithmBroader topic: It illustrates how an iterative algorithm extracts rankings from the structure of the web.

• Adjacency matrixRelated: A normalized adjacency matrix defines the transitions used by the random walk.

• Markov chainBroader topic: Its random-surfer model turns web links into transitions between page states.

• Random walkBroader topic: A web-link graph becomes a walk whose long-run visit frequencies determine page scores.

• Fixed pointBroader topic: Its scores are obtained as a fixed point of a stochastic matrix transformation.

• Search engineRelated: It contributed a signal of page authority beyond matching query words.

• Sparse matrixRelated: Its computation uses the sparse transition structure of the web graph.

• Search engine optimizationRelated: It illustrates how inbound links became signals of page importance.

• GoogleBroader topic: PageRank helped distinguish Google’s early search results from competing search engines.

• EigenvectorBroader topic: Its ranking scores are obtained from a dominant eigenvector.

• Fixed-point iterationRelated: Power iteration repeatedly applies a matrix map to approximate its defining vector.

• Google SearchBroader topic: PageRank helped establish link structure as one signal for ranking web pages.

• Larry PageBroader topic: Page developed this link-analysis method with Brin as a foundation for Google’s search ranking.

• Sergey BrinBroader topic: The algorithm grew from Brin and Page’s work on BackRub.

• Spectral radiusRelated: Its power iteration relies on spectral properties of a stochastic matrix.

• Matrix theoryBroader topic: Its defining computation finds an eigenvector of a stochastic matrix.

• Degree matrixRelated: Transition matrices for link graphs normalize outgoing links, closely related to degree-based scaling.

• Spectral graph theoryRelated: Its ranking vector is a dominant eigenvector of a modified link matrix.

• GoogleBroader topic: PageRank helped distinguish Google Search by using the web’s link structure to rank pages.