Big Data y diferentes enfoques de clustering subespacial: De la promoción en redes sociales al mapeo genómico

Vijaya Kishore Veparala; Vattikunta Kalpana

doi:10.56294/saludcyt2023413

Autores/as

Vijaya Kishore Veparala Department of ECE, Mohan Babu University, Tirupati, A.P, India https://orcid.org/0000-0003-3114-0463
Vattikunta Kalpana Department of ECE, Mohan Babu University, Tirupati, A.P, India https://orcid.org/0000-0002-7959-8433

DOI:

https://doi.org/10.56294/saludcyt2023413

Palabras clave:

Big Data, Clustering, Subespacio, Clasificación, Revisión integradora

Resumen

En la era actual de las tecnologías de la información, la información es el factor más importante para determinar cómo progresarán los distintos paradigmas. Esta información debe extraerse de un enorme tesoro informático. El aumento de la cantidad de datos analizados e interpretados es consecuencia directa de la proliferación de plataformas de procesamiento más potentes, el incremento del espacio de almacenamiento disponible y la transición hacia el uso de plataformas electrónicas. En este trabajo se describe un estudio exhaustivo de Big Data, sus características y el papel que desempeña el algoritmo de clustering Subspace. La contribución más importante que hace este trabajo es que lee muchas investigaciones anteriores y luego hace una presentación exhaustiva sobre las diferentes formas en que otros autores han clasificado los métodos de clustering subespacial. Además, se han proporcionado, con una breve explicación, algoritmos significativos que pueden servir de referencia para cualquier desarrollo futuro.

Métricas

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Citas

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