Network Algorithms, Data Mining, and Applications
NET, Moscow, Russia, May 2018
Seiten
2020
|
1st ed. 2020
Springer International Publishing (Verlag)
978-3-030-37156-2 (ISBN)
Springer International Publishing (Verlag)
978-3-030-37156-2 (ISBN)
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.
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.
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| Erscheinungsdatum | 25.02.2020 |
|---|---|
| Reihe/Serie | Springer Proceedings in Mathematics & Statistics |
| Zusatzinfo | XIII, 244 p. 65 illus., 43 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 513 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
| Mathematik / Informatik ► Mathematik ► Graphentheorie | |
| Schlagworte | clusters • combinatorics • Gaussian Graphical Model • graph dissimilarities • Information Theory • Integer programming techniques • Large-Scale Graph Clustering • Large-Scale Graph Processing Systems • Link Partitioning • Machine Learning Analysis • Metaheuristics • modeling clique relaxations • network algorithms • Network data mining • Network Science Applications • Partitioning Around Medoids • Traveling Salesman Problem |
| ISBN-10 | 3-030-37156-5 / 3030371565 |
| ISBN-13 | 978-3-030-37156-2 / 9783030371562 |
| Zustand | Neuware |
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