Network Algorithms, Data Mining, and Applications

Ilya Bychkov

ISBN 10: 303037159X / ISBN 13: 9783030371593

Editore: Springer International Publishing, Springer International Publishing Feb 2021, 2021

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Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.

Codice articolo 9783030371593

Dati bibliografici

• Titolo: Network Algorithms, Data Mining, and Applications
• Editore: Springer International Publishing, Springer International Publishing Feb 2021
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 303037159X
• ISBN 13: 9783030371593
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 15 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 15 millimetri di profondità
• Peso: 400 grammi

Descrizione articolo

Riassunto

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, and biclustering algorithms are presented with applications to social network analysis.