Descripción
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The understanding of the structure and dynamics of the intricate network of connections among people that consumes products through Internet appears as an extremely useful asset in order to study emergent properties related to social behavior. This knowledge could be useful, for example, to improve the performance of personal recommendation algorithms. In this contribution, we analyzed five-year records of movie-rating transactions provided by Netflix, a movie rental platform where users rate movies from an online catalog. This dataset can be studied as a bipartite user-item network whose structure evolves in time. | |
Internacional
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Si |
JCR del ISI
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Si |
Título de la revista
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International Journal of Bifurcation And Chaos |
ISSN
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0218-1274 |
Factor de impacto JCR
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0,755 |
Información de impacto
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Volumen
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22 |
DOI
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Número de revista
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7 |
Desde la página
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1250180 |
Hasta la página
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1250192 |
Mes
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MARZO |
Ranking
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