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Matrix theory / Markov models / Matrices / Singular value decomposition / Eigenvalues and eigenvectors / PageRank / Perron–Frobenius theorem / Eigendecomposition of a matrix / Power iteration / Algebra / Linear algebra / Mathematics


THE $25,000,000,000∗ EIGENVECTOR THE LINEAR ALGEBRA BEHIND GOOGLE KURT BRYAN† AND TANYA LEISE‡ Abstract. Google’s success derives in large part from its PageRank algorithm, which ranks the importance of webpages
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Document Date: 2006-05-08 13:33:05

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City

Philadelphia / New York / /

Company

GOOGLE / Yahoo / /

Currency

pence / USD / /

/

Event

IPO / /

Facility

Amherst College / Rose-Hulman Institute of Technology / /

/

IndustryTerm

connected web / web consisting / given web page / search result listings / Internet Tech / given web / web design / page web / irrelevant web pages / search engines / sensible web rankings / web page rankings / web context / search leads / interconnected web / search engine principles / relabelled web / search engine / web containing billions / search text / /

Organization

Mathematics and Computer Science Department / Rose-Hulman Institute of Technology / Amherst College / /

Person

Ai / TANYA LEISE / KURT BRYAN / /

/

Position

surfer / author / /

Product

V1 (A) / /

ProvinceOrState

New York / /

Technology

PageRank algorithm / search engine / ranking algorithm / /

URL

www.kurtbryan.com / www.rose-hulman.edu/∼bryan / /

SocialTag