Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected Papers. Val. 11832.

doi:10.1007/978-3-030-37334-4

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Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected Papers

Vol. 11832. Cham : Springer, 2019.

Under the general editorship: W. M. van der Aalst, Batagelj V., Ignatov D. I., Khachay M. Y., Kuskova V., A. Kutuzov, Kuznetsov S., Lomazova I. A., N. Loukachevitch, A. Napoli, Pardalos P. M., M. Pelillo, Savchenko A., E. Tutubalina

This book constitutes the post-conference proceedings of the 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019, held in Kazan, Russia, in July 2019.

The 27 full and 8 short papers were carefully reviewed and selected from 134 submissions (of which 21 papers were automatically rejected without being reviewed). The papers are organized in topical sections on general topics of data analysis; natural language processing; social network analysis; analysis of images and video; optimization problems on graphs and network structures; and analysis of dynamic behavior through event data.

Detection of Anomalies in the Criminal Proceedings Based on the Analysis of Event Logs

Alexandra Kolosova, Irina Lomazova, , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. P. 401–410.

Added: October 24, 2019

Fast Nearest-Neighbor Classiﬁer based on Sequential Analysis of Principal Components

Sokolova A., Savchenko A., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. Ch. 7 P. 73–80.

In this paper we improve the speed of the nearest neighbor classiﬁers of a set of points based on sequential analysis of high-dimensional feature vectors. Each input object is associated with a sequence of principal component scores of aggregated features extracted by deep neural network. The number of components in each element of this sequence ...

Added: October 31, 2019

Multilevel exponential random graph models application to civil participation studies

Kuskova V., Khvatsky Gregory, Zaytsev D. et al., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. P. 265–275.

Due to the development of the Internet and social networks, civil participation in political processes is taking new forms, not accounted for in the classical theoretical frameworks. In this study, we present a new methodology for researching these new, unconventional forms of civil participation. We use data collected from a social network site VK.com. Social network ...

Added: November 7, 2019

The Entity Name Identification in Classification Algorithm: Testing the Advocacy Coalition Framework by Document Analysis (The Case of Russian Civil Society Policy)

Zaytsev D., Talovsky N., Kuskova V. et al., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. P. 276–288.

This is an application of an advanced entity recognition algorithm to a large dataset. ...

Added: November 7, 2019

Authorship Attribution in Russian with New High-Performing and Fully Interpretable Morpho-Syntactic Features

Pimonova E., Durandin O., Malafeev A., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. P. 193–204.

This work tackles the problem of modeling author style in Russian. In particular, we solve the task of authorship attribution using the collected dataset of 30 authors, 1506 texts written in the period of 18th – 21st century. We apply various approaches to solving the attribution problem: Random Forest, Logistic Regression, SVM Classifier. In terms ...

Added: November 7, 2019

Multi-label Image Set Recognition in Visually-Aware Recommender Systems

Demochkin K., Savchenko A., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. Ch. 26 P. 291–297.

In this paper we focus on the problem of multi-label image recognition for visually-aware recommender systems. We propose a two stage approach in which a deep convolutional neural network is firstly fine-tuned on a part of the training set. Secondly, an attention-based aggregation network is trained to compute the weighted average of visual features in ...

Added: December 22, 2019

Double-Blind Peer-Reviewing and Inclusiveness in Russian NLP Conferences

Kutuzov A. B., Никишина И. А., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. P. 3–8.

Double-blind peer reviewing has been proved to be a pretty effective and fair way of academic work selection. However, to the best of our knowledge, nobody has yet analysed the effects caused by its introduction at the Russian NLP conferences. We investigate how the double-blind peer reviewing influences gender and location (according to authors’ affiliations) ...

Added: January 20, 2020

Log-Based Reading Speed Prediction: A Case Study on War and Peace

Igor Tukh, Braslavski P., Buraya K., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. P. 122–133.

In this exploratory study, we analyze reading behavior using logs from an ebook reading app. The logs contain users’ page turns along with time stamps and page sizes in characters. We focus on 17 readers of War and Peace by Leo Tolstoy, who read at least 80% of the novel. We aim at learning a ...

Added: February 24, 2020

Combining neural language models for word sense induction

Arefyev, N, Boris S., Aleksashina T., , in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected PapersVol. 11832.: Cham: Springer, 2019. P. 105–121.

Word sense induction (WSI) is the problem of grouping occurrences of an ambiguous word according to the expressed sense of this word. Recently a new approach to this task was proposed, which generates possible substitutes for the ambiguous word in a particular context using neural language models, and then clusters sparse bag-of-words vectors built from ...

Added: October 9, 2020

Research target: Computer Science

Priority areas: IT and mathematics

Language: English

DOI

Text on another site

Keywords: analysis of social networks big data Analysis of Images computer science AIST analysis of texts analysis of images and video

Publication based on the results of:

Development of Mathematical Models and Methods for Recommender Systems and Natural Language Processing (2019)

Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected Papers

The recognition-by-components method

Mylnikov L., Slivnitsin P., Engineering Applications of Artificial Intelligence 2026 Vol. 179 Article 115185

The paper describes a applied artificial intelligence task of recognition-by-components method of real objects based on the recognition of a limited set of primitives or components. The recognition-by-components makes it possible to determine the components, that compose an object, and increase the number of recognizable objects without degrading the recognition quality. Training is performed on ...

Added: May 29, 2026

Brain-Computer Interfaces for Gait Rehabilitation After Stroke A Scoping Review

Mokienko O., Zisman M. A., Bobrov P. et al., American Journal of Physical Medicine and Rehabilitation 2026 Vol. 105 No. 6 P. 555–563

Brain-computer interfaces (BCIs) represent a promising technology for restoring lower limb motor functions and gait after stroke. The application of BCIs in this field is supported by a limited number of studies. The objective of the review was to systematically and critically evaluate the current evidence on the use of BCIs for lower limb function ...

Added: May 28, 2026

ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ И ТЕХНИЧЕСКИЕ СРЕДСТВА УПРАВЛЕНИЯ (ICCT-2024)

М.: Институт проблем управления им. В.А. Трапезникова РАН, 2024.

В сборник вошли материалы VIII Международной научной конференции «Информационные технологии и технические средства управления» (ICCT-2024). На конференции были рассмотрены вопросы, касающиеся перспектив развития научного приборостроения в телекоммуникационных и управляющих системах, биомедицинской информатики, аппаратного и программного обеспечения информационнокоммуникационных систем, надежности, диагностики и неразрушающего контроля, систем управления и автоматизации, цифровых экосистем, управления производством и логистикой, методов математического ...

Added: May 27, 2026

Non-linear in-band interference cancellation on base of conjugate gradients method

Degtyarev A., Bakhurin S., Yudin N., DSPA 2026 P. 1–6

This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...

Added: May 26, 2026

28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy – Including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025)

IOS Press, 2025.

Added: May 26, 2026

Comparative Study of Training Methods and Architectures of Echo State Networks

Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114

This paper examines echo state networks (ESNs), one of the most prevalent approaches to implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained) weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...

Added: May 26, 2026

Рефакторинг исходного кода на основе LLM и расширения UML

Караваева Е. А., Кулигин Л. А., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 67–94

В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...

Added: May 24, 2026

Coping with AI errors with provable guarantees

Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856

AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...

Added: May 23, 2026

Overcoming the Curse of Dimensionality with Synolitic AI

Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84

High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...

Added: May 23, 2026

Stable On-the-Fly Learning for Dynamic Neural Networks With Delayed Inputs

Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392

This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...

Added: May 22, 2026

Опыт применения сетевого анализа (SNA) в историческом нарративе полисубъектного региона (на примере валлийской хроники Brut y Tywysogyon)

Loshkareva M. E., Matveeva N., Вестник Томского государственного университета. История 2026 № 100 С. 112–118

This research is an endeavor to apply social network analysis (SNA) to the study of a medieval narrative source. The authors suppose that the use of network analysis may offer new possibilities in the study of the history of regions characterized by some political fragmentation. Authors tried to construct networks of historical interactions from 1193 ...

Added: May 22, 2026

Reproducible Benchmark of Wavelet-Enhanced Intrabody Communication Biometric Identification

Jin S., Komarov M. M., Scientific Reports 2026

Intrabody communication (IBC) channels offer physiological diversity that can be leveraged for passive biometric identification in wearable devices. Recent reports of over 99 per cent identification accuracy have frequently resulted from data leakage, where samples from the same subject are seen in both training and evaluation, yielding inflated and unreliable metrics. In this work, we ...

Added: May 21, 2026

ML-based Fast Simulation of FARICH Responses

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

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)

Rabat: Association for Computational Linguistics, 2026.

Added: May 19, 2026

Dataset of solubility values for organic compounds in binary mixtures of solvents at various temperatures

Bezzubov S., Malikov D., Krasnov L. et al., Scientific data 2026 Vol. 13 Article 727

Solubility is a crucial property of organic compounds, impacting their potential applications in synthetic chemistry, materials science and drug design. Moreover, in technological processes mixtures of solvents are often utilized, making the solubility assessment more complicated. Predicting solubility values in mixtures of solvents from a molecular structure can help to address this issue, although a ...

Added: May 19, 2026

Aerokinesis: An IoT-Based Vision-Driven Gesture Control System for Quadcopter Navigation Using Deep Learning and ROS2

Kondratev S., Yulia Dyrchenkova, Georgiy Nikitin et al., Technologies 2026 Vol. 14 No. 1 Article 69

This paper presents Aerokinesis, an IoT-based software–hardware system for intuitive gesture-driven control of quadcopter unmanned aerial vehicles (UAVs), developed within the Robot Operating System 2 (ROS2) framework. The proposed system addresses the challenge of providing an accessible human–drone interaction interface for operators in scenarios where traditional remote controllers are impractical or unavailable. The architecture comprises ...

Added: May 19, 2026

Aerokinesis: An IoT-Based Vision-Driven Gesture Control System for Quadcopter Navigation Using Deep Learning and ROS2

Kondratev S., Yulia Dyrchenkova, Georgiy Nikitin et al., Technologies 2026 Vol. 14 No. 1 Article 69

Added: May 19, 2026

Parallel Computational Technologies. PCT 2025

Springer, 2025.

This book constitutes the refereed proceedings of the 19th International Conference on Parallel Computational Technologies, PCT 2025, held in Moscow, Russia, during April 8–10, 2025. The 31 full papers included in this volume were carefully reviewed and selected from 122 submissions. These papers were organized under the following topical sections: High Performance Architectures, Tools and Technologies; ...

Added: May 18, 2026

KMHCR: A Key-Controlled Signal-Domain Transformation for 5G IoT Security

Ronglin Z., Wei L., Jiahong C. et al., Journal of Signal Processing Systems 2026 Vol. 98 Article 31

To address the need for lightweight and low-latency protection in massive resource-constrained 5G Internet of Things (IoT) systems, this paper proposes Key-Controlled Modulation Hopping and Constellation Rotation (KMHCR). KMHCR is designed as a physical-layer confidentiality-enhancement mechanism that avoids bit-wise full-payload encryption in the protection pipeline. It uses a shared key derived from channel-reciprocity secret key ...

Added: May 16, 2026

DPN Verifier: A Toolkit for Faster Soundness Verification and Repair of Process Models with Data

Suvorov N. M., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3(2) P. 49–66

Data Petri Nets (DPNs) extend classical Petri nets to model processes where data directly influences control-flow, enabling a comprehensive view of system behavior and possibility to detect failure points that could otherwise be hidden. Soundness is a correctness criterion that captures such failure points as deadlocks and livelocks as well as model boundedness and absence ...

Added: May 16, 2026

Dynamic states in a network of type-I Morris-Lecar neurons characterized using the Metric Framework

Радушев Д. О., Dogonasheva O., Гуткин Б. С. et al., Chaos 2026 Vol. 36 No. 5 P. 1–10

In recent decades, analysis of dynamic states in neural networks has become an important direction of the synchronization theory. One of the most interesting neuronal network states is the chimera state, in which coherent and incoherent activity clusters coexist. While chimera states have been shown to exist in various networks, their precise automatic identification in ...

Added: May 13, 2026

QGKM: A Quantum Fidelity-Based Graph Clustering Framework for Robust Data Pattern Recognition in Education Social Networks

Xiong N., Long W., He D. et al., Algorithms 2026 Vol. 19 No. 5 Article 386

In the era of data-driven education, educational social networks generate large volumes of high-dimensional and complex-structured data through learner interactions, collaborative activities, and resource-sharing behaviors, posing significant challenges to traditional unsupervised learning methods. Such data often exhibit non-convex distributions, heterogeneity, and noise sensitivity, making conventional clustering approaches insufficient for capturing their intrinsic structural relationships. To ...

Added: May 13, 2026

Natural hazard database from Internet publications: text mining with a large language model

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

WWW '26: Proceedings of the ACM Web Conference 2026

NY: Association for Computing Machinery (ACM), 2026.

It is our great pleasure to welcome you to the 35th edition of the Web Conference to be held on June 29 – July 3, 2026, in Dubai, United Arab Emirates. Following discussions with our partners and key stakeholders, we have taken the decision to postpone the ACM Web Conference 2026, initially planned for April 2026. ...

Added: April 23, 2026