A cloud-based architecture for explainable Big Data analytics using self-structuring Artificial Intelligence

Big Data is steadily expanding beyond the boundaries of its foundational constructs of three primary Vs, Volume, Velocity and Variety, and two secondary Vs, Veracity and Value. The advent of 5G networks, Edge computing and IoT technologies has transformed Big Data into this modern context. With thes...

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Vydáno v:	Discover Artificial Intelligence Ročník 4; číslo 1; s. 33 - 13
Hlavní autoři:	Mills, Nishan, Issadeen, Zafar, Matharaarachchi, Amali, Bandaragoda, Tharindu, De Silva, Daswin, Jennings, Andrew, Manic, Milos
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.12.2024 Springer Nature B.V Springer
Témata:	Architecture Artificial Intelligence Batch processing Big Data Big Data analytics Cloud platforms Computer Science Data analysis Energy consumption Engineering Explainable AI Machine learning Real time Self structuring Artificial Intelligence Sensors Big Data analytics Self structuring Artificial Intelligence Explainable AI Cloud platforms Artificial Intelligence
ISSN:	2731-0809, 2731-0809
On-line přístup:	Získat plný text
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