img Leseprobe Leseprobe

Network Algorithms, Data Mining, and Applications

NET, Moscow, Russia, May 2018

Oleg Prokopyev (Hrsg.), Panos M. Pardalos (Hrsg.), Valery A. Kalyagin (Hrsg.), Ilya Bychkov (Hrsg.)

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Sonstiges

Beschreibung

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.

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Schlagwörter

Large-Scale Graph Processing Systems, Gaussian graphical model, Partitioning Around Medoids, Information Theory, Network algorithms, Large-Scale Graph Clustering, Network data mining, Link Partitioning, Integer programming techniques, Machine Learning Analysis, combinatorics, modeling clique relaxations, Clusters, Traveling Salesman Problem, graph dissimilarities, Network Science Applications, Metaheuristics