Computational Aspects and Applications in Large-Scale Networks, 1st ed. 2018
NET 2017, Nizhny Novgorod, Russia, June 2017
Springer Proceedings in Mathematics & Statistics Series, Vol. 247

Contributions in this volume focus on computationally efficient algorithms and rigorous mathematical theories for analyzing large-scale networks. Researchers and students in mathematics, economics, statistics, computer science and engineering will 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.

Part I: Network computational algorithms

1.               Tabu Search for Fleet Size and Mix Vehicle Routing Problem with Hard and Soft Time Windows

3.               The Video-Based Age and Gender Recognition with Convolution Neural Networks

Angelina Kharchevnikova and Andrey Savchenko  

4.               On forbidden induced subgraphs for the class of triangle-Konig graphs

Dmitry B. Mokeev     

5.               The Global Search Theory Approach to the Bilevel Pricing Problem in Telecommunication Networks

Andrei Orlov 

6.               Graph dichotomy algorithm and its applications to analysis of stocks market

Alexander Rubchinsky

7.               Cluster analysis of facial video data in video surveillance systems using deep learning

Anastasiia Sokolova and Andrey Savchenko

8.               Using modular decomposition technique to solve the maximum clique problem

Irina Utkina

Part II: Network Models

9.               Robust statistical procedures for testing dynamics in market network

Alexander Koldanov and Maria Voronina   

10.            Application of Market Models to Network Equilibrium Problems

Igor Konnov   

11.            Selective Bi-coordinate Variations for Network Equilibrium Problems with Mixed Demand

Igor Konnov and Olga Pinyagina      

12.            Developing a Model of Topological Structure Formation for Power Transmission Grids Based on the Analysis of the UNEG

Sergey Makrushin     

13.            Methods of criteria importance theory and their software implementation

Andrey Nelyubin, Vladislav Podinovski and Mikhail Potapov       

14.            A Model of Optimal Network Structure for Decentralized Nearest Neighbor Search

Alexander Ponomarenko, Irina Utkina and Mikhail Batsyn

15.            Computational Study of Activation Dynamics on Networks of Arbitrary Structure

Alexander Semenov, Dmitry Gorbatenko and Stepan Kochemazov

16.            Rejection graph for multiple testing of elliptical model for market network

Dmitry Semenov and Petr Koldanov

17.            Mapping Paradigms of Social Sciences: application of network analysis

Dmitry Zaytsev and Daria Drozdova

Part III: Network Applications

18.            Using Geometry of the Set of Symmetric Positive Semidefinite Matrices to Classify Structural Brain Networks

19.            Comparison of statistical procedures for Gaussian graphical model selection

Ivan Grechikhin and Valery Kalyagin

20.            Sentiment Analysis Using Deep Learning

Nikolay Karpov and Alexander Lyashuk and Arsenii Vizgunov

21.            Invariance properties of statistical procedures for network structures identification

Petr Koldanov

22.            Topological modules of human brain networks are anatomically embedded: evidence from modularity analysis at multiple scales

Anvar Kurmukov, Yulia Dodonova, Margarita Burova, Ayagoz Mussabayeva, Dmitry Petrov, Joshua Faskowitz and Leonid Zhukov         

23.            Commercial Astroturfing Detection in Social Networks

Nadezhda Kostyakova, Ilia Karpov, Ilya Makarov and Leonid E. Zhukov  

24.            Information Propagation Strategies in Online Social Networks

Rodion Laptsuev, Marina Ananyeva, Dmitry Meinster, Ilia Karpov, Ilya Makarov and Leonid E. Zhukov

25.            Analysis of co-authorship networks and scientific citation based on Google Scholar

Nataliya Matveeva and Oleg Poldin 

26.            Company Co-Mention Network Analysis

Sergei Sidorov, Alexey Faizliev, Vladimir Balash, Alexandr Gudkov, Alfia Chekmareva and Pavel Anikin    

Presents state-of-the-art techniques in modern network analysis for large-scale networks

Features new theoretical models, approaches, and tools for network analysis

Broadens understanding of computationally efficient algorithms