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Network Algorithms, Data Mining, and Applications

NET, Moscow, Russia, May 2018
BuchKartoniert, Paperback
244 Seiten
Englisch
Springererschienen am23.02.20211st ed. 2020
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.mehr
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BuchGebunden
EUR106,99
BuchKartoniert, Paperback
EUR106,99

Produkt

KlappentextComputational 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.
Details
ISBN/GTIN978-3-030-37159-3
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2021
Erscheinungsdatum23.02.2021
Auflage1st ed. 2020
ReiheSpringer Proceedings in Mathematics & Statistics
Seiten244 Seiten
SpracheEnglisch
IllustrationenXIII, 244 p. 65 illus., 43 illus. in color.
Artikel-Nr.49370217

Inhalt/Kritik

Inhaltsverzeichnis
Part I: Network algorithms.- Obaid, H. B. and Trafalis, T: Fairness in Resource Allocation: Foundation and Applications.- Ignatov, D., Ivanova, P., Zamaletdinova, A. and Prokopyev, O: Searching for Maximum Quasi-Bicliques with Mixed Integer Programming.- Miasnikof, P., Pitsoulis, L., Bonner, A. J., Lawryshyn, Y. and Pardalos, P. M: Graph Clustering Via Intra-Cluster Density Maximization.- Shvydun, S.: Computational Complexity of SRIC and LRIC indices.- Sifaleras, A. and Konstantaras, I: A survey on variable neighborhood search methods for supply network inventory.- Part II: Network Data Mining.- Ananyeva, M. and Makarov, I: GSM: Inductive Learning on Dynamic Graph Embeddings.- Averchenkova, A., Akhmetzyanova, A., Sudarikov, K., Sulimov, P., Makarov I. and Zhukov, L. E:  Collaborator Recommender System based on Co-authorship Network Analysis.- Demochkin, K. and Savchenko, A: User Preference Prediction in a Set of Photos based on Neural Aggregation Network.- Makrushin , S.: Network structure and scheme analysis of the Russian language segment of Wikipedia.- Meshcheryakova, N., Shvydun, S. and Aleskerov, F: Indirect Influence Assessment in the Context of Retail Food Network.- Sokolova, A. D. and Savchenko, A. V: Facial clustering in video data using deep convolutional neural networks.- Part III: Network Applications.- Egamov, A.: The existence and uniqueness theorem for initial-boundary value problem of the same class of integro-differential PDEs.- Gradoselskaya, G., Karpov, I. and Shcheglova, T: Mapping of politically active groups on social networks of Russian regions (on the example of Karachay-Cherkessia Republic).- Mikhailova, O., Gradoselskaya, G. and Kharlamov, A: Social Mechanisms of the Subject Area Formation. The Case of Digital Economy.- Shcheglova, T., Gradoselskaya, G. and Karpov, I: Methodology for measuring polarization of political discourse: case of comparing oppositional and patriotic discourse in online social networks.- Zaytsev, D., Khvatsky, G., Talovsky, N. and Kuskova, V: Network Analysis Methodology of Policy Actors Identification and Power Evaluation (the case of the Unified State Exam introduction in Russia).mehr

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