Springer Proceedings in Mathematics & Statistics- Network Algorithms, Data Mining, and Applications NET, Moscow, Russia, May 2018

  • en
  • Couverture rigide
  • 9783030371562
  • 23 février 2020
  • 244 pages
Toutes les spécifications de l'article

Résumé

Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks.

This proceedings presents the result of the 8th International Conference in Network Analysis, held at the Higher School of Economics, Moscow, in May 2018. The conference brought together scientists, engineers, and researchers from academia, industry, and government.
Contributions in this book focus on the development of network algorithms for data mining and its applications. Researchers and students in mathematics, economics, statistics, computer science, and engineering find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks. Machine learning techniques in network settings including community detection, clustering, andbiclustering algorithms are presented with applications to social network analysis.

This proceedings presents the result of the 8th International Conference in Network Analysis, held at the Higher School of Economics, Moscow, in May 2018. The conference brought together scientists, engineers, and researchers from academia, industry, and government.
Contributions in this book focus on the development of network algorithms for data mining and its applications. Researchers and students in mathematics, economics, statistics, computer science, and engineering find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks. Machine learning techniques in network settings including community detection, clustering, andbiclustering algorithms are presented with applications to social network analysis.

Spécifications produit

Contenu

Langue
en
Version
Couverture rigide
Date de sortie initiale
23 février 2020
Nombre de pages
244
Illustrations
Non

Personnes impliquées

Rédacteur en chef
Ilya Bychkov
Deuxième rédacteur
Valery A. Kalyagin
Coéditeur
Panos M. Pardalos
Editeur principal
Springer Nature Switzerland AG

Informations sur le fabricant

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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
559 g
Police de caractères extra large
Non
Édition
1st ed. 2020

EAN

EAN
9783030371562

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