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Intelligent Systems in Big Data Semantic Web and Machine Learning

Intelligent Systems in Big Data Semantic Web and Machine Learning

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The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. This book describes important methodologies, tools and techniques from the fields of artificial intelligence, basically those which are based on relevant conceptual and formal development. The coverage is wide, ranging from machine learning to the use of data on the Semantic Web, with many new topics. The contributions are concerned with machine learning, big…

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SKU: CIAPEEH0736962404779
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Description

The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. This book describes important methodologies, tools and techniques from the fields of artificial intelligence, basically those which are based on relevant conceptual and formal development. The coverage is wide, ranging from machine learning to the use of data on the Semantic Web, with many new topics. The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. The book is meant to be a very important and useful source of information for researchers and doctoral students in data analysis, Semantic Web, big data, machine learning, computer engineering and related disciplines, as well as for postgraduate students who want to integrate the doctoral cycle.

Langue
en
Version
Couverture rigide
Date de sortie initiale
29 mai 2021
Nombre de pages
315
Illustrations
Avec illustrations

Personnes impliquées

Auteur principal

Noreddine Gherabi

Deuxième auteur

Janusz Kacprzyk

Rédacteur en chef

Noreddine Gherabi

Deuxième rédacteur

Janusz Kacprzyk

Editeur principal

Springer Nature Switzerland AG

Informations sur le fabricant

Nom du fabricant
Springer Nature Customer Service Center GmbH
Adresse du fabricant
– 69115 – – DE
Adresse électronique du fabricant
ProductSafety@springernature.com
Informations sur le fabricant
Les informations du fabricant ne sont actuellement pas disponibles

Autres spécifications

Hauteur de l’emballage
235 mm
Largeur d’emballage
155 mm
Largeur du produit
155 mm
Livre d‘étude
Non
Longueur d’emballage
235 mm
Longueur du produit
235 mm
Poids de l’emballage
664 g
Édition
1st ed. 2021

EAN

EAN
9783030725877

Sécurité des produits

Opérateur économique responsable dans l’UE

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Catégories

Ordinateurs et Informatique

Technologies informatiques

Bases de données

Intelligence artificielle

Apprentissage automatique

Livres

Livre, ebook ou livre audio ?

Livre

Disponibilité

Disponible à l’adresse suivante

Langue

Anglais

Type de livre

Hardcover

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