Network Algorithms, Data Mining, and Applications : NET, Moscow, Russia, May 2018. 1st ed. 2020

種類:

電子ブック

責任表示:

edited by Ilya Bychkov, Valery A. Kalyagin, Panos M. Pardalos, Oleg Prokopyev

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2020

著者名:

• Bychkov, Ilya.
• Kalyagin, Valery A.
• Pardalos, Panos M.
• Prokopyev, Oleg.
• SpringerLink (Online service)

シリーズ名:

Springer Proceedings in Mathematics & Statistics ; 315

ISBN:

9783030371579 [3030371573]    

注記:

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 schem
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

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