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Multisorgente Eterogeneo Grafico Grandi dati Apprendimento della rappresentazione

Multisorgente Eterogeneo Grafico Grandi dati Apprendimento della rappresentazione

Xun Liang

84,64 €
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Editorial:
KS OmniScriptum Publishing
Año de edición:
2022
Materia
Empresa y gestión
ISBN:
9786205369739
84,64 €
IVA incluido
Disponible

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La grande quantità di dati accumulati e complessi comporta anche sfide per l’interrogazione e l’elaborazione. Con l’aggiornamento dei dati, il numero di nodi e bordi contenuti nel grafo può diventare sempre più grande. Il numero di nodi nei dati di struttura a grafo su larga scala può raggiungere milioni o addirittura centinaia di milioni e presenta le caratteristiche di multisorgente, eterogeneità, isomerizzazione e dinamica.I big data eterogenei a più fonti possono spesso essere modellati in una struttura di dati a grafo con l’apprendimento della rappresentazione. Il grafo di rete complesso ha normalmente alcune particolarità, che aumentano la difficoltà della ricerca. Il modello di apprendimento della rappresentazione dei dati a grafo eterogeneo complesso su larga scala ha un’ampia gamma di applicazioni in molti campi. Questo libro affronta questi modelli di apprendimento di rappresentazione dei dati a grafo eterogeneo multisorgente e le loro applicazioni nel campo della sicurezza pubblica.

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