Las matemáticas del algoritmo PageRank
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[ES] En 1998, Larry Page y Sergey Brin revolucionaron la eficiencia de los motores de búsqueda web con la creación del algoritmo PageRank, todavía hoy usado por el motor de búsqueda de Google. A principios de los años 90, los motores de búsqueda usaban sistemas de clasificación basados en texto para decidir qué páginas eran más relevantes para una consulta dada. La idea que el algoritmo PageRank sacó a colación fue que la importancia de cualquier página web puede ser juzgada observando el número y la autoridad de las páginas que enlazan con ella. Traduciendo estas palabras en términos matemáticos entra en juego el álgebra lineal, mientras que la teoría de grafos y las cadenas de Markov están en la esencia del algoritmo.
[EN] In 1998, Larry Page and Sergey Brin revolutionized the efficiency of web search engines by creating the PageRank algorithm, still used by Google’s search engine today. In the early 90s, the search engines used text-based ranking systems to decide which pages are most relevant to a given query. The idea that PageRank brought up was that the importance of any web page could be judged by looking at the number and authority of the pages that link to it. Translating these words into mathematical terms brings linear algebra into play, while graph theory and Markov chains are at the heart of the algorithm.
[EN] In 1998, Larry Page and Sergey Brin revolutionized the efficiency of web search engines by creating the PageRank algorithm, still used by Google’s search engine today. In the early 90s, the search engines used text-based ranking systems to decide which pages are most relevant to a given query. The idea that PageRank brought up was that the importance of any web page could be judged by looking at the number and authority of the pages that link to it. Translating these words into mathematical terms brings linear algebra into play, while graph theory and Markov chains are at the heart of the algorithm.
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Traballo Fin de Grao en Matemáticas. Curso 2019-2020
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