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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science

Vol. 11179. Berlin : Springer, 2018.
Under the general editorship: W. M. van der Aalst, Batagelj V., G. Glavaš,, Ignatov D. I., M. Khachay, O. Koltsova, Kuznetsov S., Lomazova I. A., N. Loukachevitch,, A. Napoli,, Savchenko A., A. Panchenko,, Pardalos P. M., M. Pelillo,

This book constitutes the proceedings of the 7th International Conference on Analysis of Images, Social Networks and Texts, AIST 2018, held in Moscow, Russia, in July 2018.

The 29 full papers were carefully reviewed and selected from 107 submissions (of which 26 papers were rejected without being reviewed). The papers are organized in topical sections on natural language processing; analysis of images and video; general topics of data analysis; analysis of dynamic behavior through event data; optimization problems on graphs and network structures; and innovative systems.

Chapters
Co-authorship Network Embedding and Recommending Collaborators via Network Embedding
Makarov I., Gerasimova O., Sulimov P. et al., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. P. 32–38.
Co-authorship networks contain invisible patterns of collaboration among researchers. The process of writing joint paper can depend of different factors, such as friendship, common interests, and policy of university. We show that, having a temporal co-authorship network, it is possible to predict future publications. We solve the problem of recommending collaborators from the point of ...
Added: September 5, 2018
Joint Node-Edge Network Embedding for Link Prediction
Makarov I., Gerasimova O., Sulimov P. et al., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. P. 20–31.
In this paper, we consider new formulation of graph embedding algorithm, while learning node and edge representation under common constraints. We evaluate our approach on link prediction problem for co-authorship network of HSE researchers’ publications. We compare it with existing structural network embeddings and feature-engineering models. ...
Added: September 5, 2018
Visualization of Data Science Community in Russia.
Yavorskiy R., Voznesenskaya T., Рудаков К. А., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. Ch. 1 P. 3–9.
We present in the form of two visualizations some preliminary results of the ongoing study of data science community in Russia. The rst visualization aggregates data about top researches and their elds of interest according to the Google Scholar service. The second graph is a map of the largest online communities on date science on ...
Added: October 4, 2018
Organizational networks revisited: Predictors of headquarters-subsidiary relationship perception
Milekhina A., Artyukhova E., Kuskova V., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. P. 39–50.
The problem of effective management of company subsidiaries has been on the forefront of strategic management research since early mid-1980s. Recently, special attention is being paid to the effect of headquarters - subsidiary conflicts on the company performance, especially in relation to the subsidiaries’ resistance, both active and passive, to following the directives of the ...
Added: October 26, 2018
Emotion Recognition of a Group of People in Video Analytics Using Deep Off-the-Shelf Image Embeddings
Tarasov Alexander V., Savchenko A., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. Ch. 19 P. 191–198.
In this paper we address the group-level emotion classification problem in video analytic systems.We propose to apply the MTCNN face detector to obtain facial regions on each video frame. Next, off-the-shelf image features are extracted from each located face using preliminary trained convolutional neural networks. The features of the whole frame are computed as a ...
Added: December 12, 2018
Application of Fully Convolutional Neural Networks to Mapping Industrial Oil Palm Plantations
Baklanov A., Khachay M., Pasynkov M., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. P. 155–167.
This research is motivated by sustainability problems of oil palm expansion. Fast-growing industrial Oil Palm Plantations (OPPs) in the tropical belt of Africa, Southeast Asia and parts of Brazil lead to significant loss of rainforest and contribute to the global warming by the corresponding decrease of carbon dioxide absorption. We propose a novel approach to ...
Added: January 23, 2019
Extraction of Visual Features for Recommendation of Products via Deep Learning
Andreeva E., Ignatov D. I., Grachev A. et al., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. P. 201–210.
In this paper (The first author is the 1st place winner of the Open HSE Student Research Paper Competition (NIRS) in 2017, Computer Science nomination, with the topic “Extraction of Visual Features for Recommendation of Products”, as alumni of 2017 “Data Science” master program at Computer Science Faculty, HSE, Moscow), we describe a special recommender ...
Added: January 23, 2019
Tree-Based Ensembles for Predicting the Bottomhole Pressure of Oil and Gas Well Flows
Ignatov D. I., Sinkov K., Spesivtsev P. et al., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. P. 221–233.
In this paper, we develop a predictive model for the multi-phase wellbore flows based on ensembles of decision trees like Random Forest or XGBoost. The tree-based ensembles are trained on the time series of different physical parameters generated using the numerical simulator of the full-scale transient wellbore flows. Once the training is completed, the ensemble ...
Added: January 23, 2019
Generic Distributed In Situ Aggregation for Earth Remote Sensing Imagery
Rodriges Zalipynis R. A., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. P. 331–342.
Earth remote sensing imagery come from satellites, unmanned aerial vehicles, airplanes, and other sources. National agencies, commercial companies, and individuals across the globe collect enormous amounts of such imagery daily. Array DBMS are one of the prominent tools to manage and process large volumes of geospatial imagery. The core data model of an array DBMS is an ...
Added: January 27, 2019
Lookup Lateration: Mapping of Received Signal Strength to Position for Geo-Localization in Outdoor Urban Areas
Shestakoff A., Kertesz-Farkas A., Shmelkin D. et al., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. P. 234–246.
The accurate geo-localization of mobile devices based upon received signal strength (RSS) in an urban area is hindered by obstacles in the signal propagation path. Current localization methods have their own advantages and drawbacks. Triangular lateration (TL) is fast and scalable but employs a monotone RSS-to-distance transformation that unfortunately assumes mobile devices are on the ...
Added: February 7, 2019
Echo chambers vs opinion crossroads in news consumption on social media
Dokuka S., Koltsov S., Koltsova O. et al., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. P. 13–19.
Social media are often conceived as a mechanism of echo-chamber for- mation. In this paper we show that in the Russian context this effect is limited. Specifically, we show that audiences of media channels represented in the lead- ing Russian social network VK, as well as their activities, significantly overlap. The audience of the oppositional ...
Added: March 1, 2021
Research target: Computer Science Mathematics
Priority areas: IT and mathematics mathematics
Language: English
Full text
DOI
Text on another site
Keywords: social networkssemanticsnatural language processingneural networkssupport vector machinesNLPWorld Wide Web information retrievalartificial intelligenceMedical image segmentation problem solvingAISTsocial networkingSVMimage processing
Publication based on the results of:
Well-interpretable Methods of Knowledge Discovery and Knowledge Representation (2018)
Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science
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