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Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics
Vol. 247.
Springer, 2018.
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.
This proceeding is a result of the 7th International Conference in Network Analysis, held at the Higher School of Economics, Nizhny Novgorod in June 2017. The conference brought together scientists, engineers, and researchers from academia, industry, and government.
Chapters
Kostyakova Nadezhda, Karpov I., Makarov I. et al., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 309–318.
One of the major problem of recommendation services is commercial astroturfing. This work is devoted to constructing a model capable of detecting astroturfing based on network analysis. The main idea of the model is projecting a multipartite network to a unipartite and detecting communities in it representing actors with falsified opinions. ...
Added: October 11, 2017
Laptsuev Rodion, Ananyeva Marina, Meinster Dmitry et al., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 319–328.
Online social networks play major role in the spread of information on a very large scale. One of the major problems is to predict information propagation using social network interactions. The main purpose of this paper is to construct heuristic model of weighted graph based on empirical data that can outperform the existing models. We ...
Added: October 11, 2017
Utkina I. E., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 121–131.
In this article we use the modular decomposition technique for exact solving the weighted maximum clique problem. Our algorithm takes the modular decomposition tree from the paper of Tedder et. al. and finds solution recursively. Also, we propose algorithms to construct graphs with modules. We show some interesting results, comparing our solution with Ostergards algorithm ...
Added: October 18, 2017
Ponomarenko A., Irina Utkina, Mikhail Batsyn, , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 197–203.
One of the approaches for the nearest neighbor search problem is to build a network which nodes correspond to the given set of indexed objects. In this case the search of the closest object can be thought as a search of a node in a network. A procedure in a network is called decentralized if ...
Added: October 18, 2017
Grechikhin I., Kalyagin V. A., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 269–279.
Graphical models are used in a variety of problems to uncover hidden structures. There is an important number of different identification procedures to recover graphical model from observations. In this paper, undirected Gaussian graphical models are considered. Some Gaussian graphical model identification statistical procedures are compared using different measures, such as Type I and Type ...
Added: October 20, 2017
Karpov N., Ляшук А. Ю., Vizgunov A. N., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 281–288.
The study was aimed to analyze advantages of the Deep Learning methods over other baseline machine learning methods using sentiment analysis task in Twitter. All the techniques were evaluated using a set of English tweets with classification on a five-point ordinal scale provided by SemEval-2017 organizers. For the implementation, we used two open source Python ...
Added: November 22, 2017
Kurmukov A., Dodonova Y., Burova M. et al., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 299–308.
Human brain networks show modular organization: cortical regions tend to form densely connected modules with only weak inter-modular connections. However, little is known on whether modular structure of brain networks is reliable in terms of test-retest reproducibility and, most importantly, to what extent these topological modules are anatomically embedded. To address these questions, we use ...
Added: December 15, 2017
Zaytsev D., Drozdova D., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 235–253.
In this paper, we propose to utilize the methods of network analysis to analyze the relationship between various elements that constitute any particular research in social sciences. Four levels that determine a design of the research can be established: ontological and epistemological assumptions that determine what is the reality under the study and how can ...
Added: August 30, 2018
Savchenko A., Kharchevnikova Angelina S., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 37–46.
The paper reviews the problem of age and gender recognition methods for video data using modern deep convolutional neural networks. We present the comparative analysis of classifier fusion algorithms to aggregate decisions for individual frames. We implemented the video-based recognition system with several aggregation methods to improve the age and gender identification accuracy. The experimental ...
Added: September 2, 2018
Savchenko A., Sokolova Anastasiia D., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 113–120.
In this paper, we propose the approach of structuring information in video surveillance systems by grouping the videos, which contain identical faces. First, the faces are detected in each frame and features of each facial region are extracted at the output of preliminarily trained deep convolution neural networks. Second, the tracks that contain identical faces ...
Added: September 2, 2018
Semenov D., Koldanov P., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 221–234.
Market network analysis attracts a growing attention last decade. Important component of the market network is a model of stock returns distribution. Elliptically contoured distributions are popular as probability model of stock returns. The question of adequacy of this model to real market data is open. There are known results that reject such model and ...
Added: September 24, 2018
Matveeva N., Poldin O. V., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 329–339.
In this study, we investigated how scientific collaboration represented by co-authorship is related to citation indicators of a scientist. We use co-authorship network to explore the structure of scientific collaboration. For network construction, the profiles of scientists from various countries and scientific fields in Google Scholar were used. We ran the count data regression model ...
Added: September 27, 2018
Koldanov A. P., Voronina M., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 135–142.
Market network analysis attracts a growing attention last decades. One of the most important problems related with it is the detection of dynamics in market network. In the present paper, the stock market network of stock’s returns is considered. Probability of sign coincidence of stock’s returns is used as the measure of similarity between stocks. ...
Added: October 11, 2018
Koldanov P., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 289–297.
Invariance properties of statistical procedures for threshold graph identification are considered. An optimal procedure in the class of invariant multiple decision procedures is constructed. ...
Added: October 11, 2018
Mikhail Batsyn, Ilya Bychkov, Larisa Komosko et al., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 3–18.
The paper presents a tabu search heuristic for the Fleet Size and Mix Vehicle Routing Problem (FSMVRP) with hard and soft time windows. The objective function minimizes the sum of travel costs, fixed vehicle costs, and penalties for soft time window violations. The algorithm is based on the tabu search with several neighborhoods. The main ...
Added: October 23, 2018
Gribanov D., , in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & StatisticsVol. 247.: Springer, 2018. P. 19–35.
In this paper, we present FPT algorithms for special cases of the shortest vector problem (SVP) and the integer linear programming problem (ILP), when matrices included in the problems’ formulations are near square. The main parameter is the maximal absolute value of rank minors of matrices included in the problem formulation. Additionally, we present FPT ...
Added: February 17, 2019
Keywords: network analysiscliquesComputational Aspects and Applications of Large Scale NetworksCritical LinksAutoregressive ModelsEquilibrium Under Network ConstraintsQuasi-cliquesClustering CoefficientRandom GraphsGuarantee NetworksNeural NetworkComplexity of GraphsVehicle Routing ProblemsTriangle-Konig GraphsInteger Linear Programming ProblemsBilevel Pricing ProblemGraph Dichotomy AlgorithmGaussian Graphical Model
Shabanov N., Kuricheva O., Kurbatova J. et al., / Series Working Papers SSRN "Department of Economics Ca’ Foscari University of Venice". 2026.
The carbon balance of an ecosystem is the difference between Gross Primary Productivity (GPP) and Ecosystem Respiration (Reco) as expressed by Net Ecosystem Exchange (NEE). While remote sensing retrievals of GPP have reached maturity, Reco estimation remains underexplored and ultimately cast bias on NEE. Here we present an end-to-end multi-scale analysis of the mechanism of ...
Added: August 21, 2026
Ponomarenko A., / Series Computer Science "arxiv.org". 2025.
This paper addresses the challenge of merging hierarchical navigable small world (HNSW) graphs, a critical operation for distributed systems, incremental indexing, and database compaction. We propose three algorithms for this task: Naive Graph Merge (NGM), Intra Graph Traversal Merge (IGTM), and Cross Graph Traversal Merge (CGTM). These algorithms differ in their approach to vertex selection ...
Added: July 30, 2026
Piontkovski D., / Series arXiv "math". 2026.
A noncommutative projective variety is defined, following Artin and Zhang, by a graded coherent algebra 𝐴. The category of coherent sheaves is then the quotient qgr(𝐴) of the category of finitely presented graded modules by the subcategory of torsion modules. We consider the categorical and polynomial entropies of the Serre twist, that is, of the ...
Added: June 23, 2026
Piontkovski D., / Series arXiv "math". 2025.
If a symmetric multilinear algebra is weakly nil, then it is Engel. This result may be regarded as an infinite-dimensional analogue of the well-known Jacobian theorem, which states that if a polynomial mapping has a polynomial inverse, then its Jacobian matrix is invertible. This refines a theorem of Gerstenhaber and partially answers a question posed ...
Added: June 23, 2026
Tyuryakova-Matveeva D., Цифровые гуманитарные исследования 2026 № 1 С. 4–26
The article explores cultural references in the works of Andrei Voznesensky by analyzing the personalities he mentions. A total of 1,678 works were processed, including poetry, prose, and early unpublished poems. NER methods based on Natasha, spaCy, and LLM Grok tools made it possible to study the frequency of mentions of famous people and their ...
Added: May 31, 2026
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Aleskerov F. T., Khutorskaya O., Stepochkina A. et al., Springer, 2026.
The book contains new models of bibliometric analysis based on centrality measures in network analysis, pattern analysis and stability analysis. A distinctive feature of these centrality measures is that they account for the parameters of vertices and group influence of vertices to a vertex. This reveals specific groups of publications, authors, terms, journals and affiliations ...
Added: May 15, 2026
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026
Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.
We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Svendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for two models in different universality classes: the Ising model and the Potts model with three components. The overlap of two ...
Added: April 20, 2026
Gabdullin N., Androsov I., / Series Computer Science "arxiv.org". 2026.
Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we show that if NN latent space (LS) geometry is known and possesses specific properties, label prediction complexity can ...
Added: April 2, 2026
Pakhomova A., Вестник Московского университета. Серия 9: Филология 2026 № 1 С. 162–177
Beginning in the mid-1920s Aleksandr Vvedensky, Daniil Kharms,
and Konstantin Vaginov became acquainted with the circle of the poet, writer, and
playwright Mikhail Kuzmin, and by the close of this decade, they became regular
visitors to his residence. The interactions between Kuzmin and the Oberiuts has
been sufficiently developed; however, numerous studies have shifted the focus to the
pragmatics of ...
Added: April 1, 2026
Barkhatova L., В кн.: Человек в информационном обществе: сборник материалов третьей международной научно-практической конференции, посвящённой 80-летию Победы в Великой Отечественной войне, 23–26 апреля 2025 года, г. Самара.: Самара: Самарский национальный исследовательский университет имени академика С.П. Королева, 2025. С. 94–98.
The analytical possibilities of using semantic network analysis in qualitative research are considered. A scheme for constructing a semantic map and its integration with the results of the qualitative stage is proposed. It is shown that the implementation of semantic networks for analyzing qualitative data enables validation of conclusions. ...
Added: January 25, 2026
Sorokin K., Beketov M., Онучин А. et al., / arxiv.org. Серия cs.SI "Social and Information Networks ". 2025.
Community detection in complex networks is a fundamental problem, open to new approaches in various scientific settings. We introduce a novel community detection method, based on Ricci flow on graphs. Our technique iteratively updates edge weights (their metric lengths) according to their (combinatorial) Foster version of Ricci curvature computed from effective resistance distance between the ...
Added: January 15, 2026
Petrovanov I., Sergeev A., / Series Computer Science "arxiv.org". 2025. No. 2512.18332.
Transport coding reduces message delay in packet-switched networks by introducing controlled redundancy at the transport layer: original packets are encoded into coded packets, and the message is reconstructed after the first successful deliveries, effectively shifting latency from the maximum packet delay to the -th order statistic. We present a concise, reproducible discrete-event implementation of transport coding in OMNeT++, including ...
Added: December 24, 2025
Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset
Меньшиков И. А., Бернадотт А. К., Elvimov N. S., / Series arXie "Statistical mechanics". 2025.
Accurate segmentation of blood vessels in brain magnetic resonance angiography (MRA) is essential for successful surgical procedures, such as aneurysm repair or bypass surgery. Currently, annotation is primarily performed through manual segmentation or classical methods, such as the Frangi filter, which often lack sufficient accuracy. Neural networks have emerged as powerful tools for medical image ...
Added: December 1, 2025
Nazarova V., Lodiagin B., Круглов Ф. А. et al., AlterEconomics (ранее - Журнал экономической теории) 2025 № 22(3) С. 482–502
This paper examines methods for forecasting oil prices, comparing traditional autoregressive mo dels (ARIMA, SARIMAX) with machine learning approaches (LSTM). The target variable is the price of WTI crude oil. The dataset covers 2015–2019 and includes both WTI price data and a set of exogenous varia bles: the Wilshire 5000, Dow Jones, and DXY indices; ...
Added: October 5, 2025
Андриянов Д. А., Брагина А. Б., Kechik U. et al., Полития: Анализ. Хроника. Прогноз 2025 Т. 118 № 3 С. 80–107
It has long been generally accepted in Political Science that distributed elite networks, rather than institutions, are crucial to the functioning of the Russian political system. One of the important factors in the formation of such networks is ethnicity. Of particular interest is the ethnic dynamics in those regions, where there is no dominant ethnic ...
Added: September 25, 2025
Andronova E., Kapuza A., Психологические исследования: электронный научный журнал 2025 Т. 18 № 102 Статья 3
This study examines concepts as systemic elements within a conceptual structure, drawing on the theoretical framework of L.S. Vygotsky’s cultural-historical psychology. A key characteristic of concepts is their level of abstraction, which reflects their degree of generalization within a system. However, existing classification methods lack a unified approach, complicating empirical research. The current study aimed ...
Added: September 19, 2025
Глумов Ф. В., Maltsev A., Terra Politica 2025 № 1 С. 167–186
The present study is devoted to the phenomenon of gerrymandering on the example of US Congressional elections. The boundaries of US Congressional electoral districts were used for the analysis. The division of states into districts was based on census data from 2000 to 2020. Data on small administrative units (counties) similarly relied on census data. ...
Added: August 6, 2025
Loseva A., Moroz A., Shmidt E. et al., International Journal of Communication 2024 Vol. 18 P. 1–26
In light of the “gardening” of the public sphere in autocracies, the question of how power is distributed in the media field calls for empirical investigation. We use computational methods of network analysis, topic modeling, and semantic analysis to test if the Russian media landscape is organized around the three “publics” as suggested by earlier ...
Added: July 7, 2025
Spinazzola M., Scuotto V., Pironti M. et al., Small Business Economics 2025 Vol. 65 P. 1517–1534
Entrepreneurial ecosystems (EEs) are regarded as ideal breeding ground for knowledge-intensive entrepreneurs (KIEs). Yet, as EEs are mostly considered isolated from each other and their connectedness is neglected, there is a lack of research on their capacity to attract KIEs rather than to locally nurturing them. Inadequate data has been a major obstacle to this ...
Added: June 30, 2025
Fuad Aleskerov, Tkachev D., , in: In Honor of the 70th Birthday of Panos Pardalos. Theory, Algorithms and Experiments in Applied Optimization. SOIA, volume 226Vol. 226.: Springer, 2025. Ch. 2 P. 22–37.
New centrality indices Bundle and Pivotal, were introduced to identify key vertices taking into account parameters of vertices and an influence of vertices to a vertex. However, the Bundle and Pivotal indices are constructed in that way that they do not take into account directly the weights of arcs – important information about interaction among vertices ...
Added: April 29, 2025
Алкзир Н., Yarykina n., Nikolaev D. et al., Neuroscience and Behavioral Physiology 2024
Added: April 28, 2025
Mikhaylova O., Dokuka S., Quality and Quantity 2025 Vol. 59 P. 4077–4095
This paper explores the use of the Core Discussion Network (CDN) methodology for analyzing personal networks. We discuss the method’s origins and the specifics of its implementation, followed by a brief overview of findings from international studies. Using data collected in 2021 from 270 first-year undergraduate and graduate students at a top-tier Russian university, we ...
Added: April 19, 2025