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News
April 30, 2026
HSE Researchers Compile Scientific Database for Studying Childrens Eating Habits
The database created at HSE University can serve as a foundation for studying children’s eating habits. This is outlined in the study ‘The Influence of Age, Gender, and Social-Role Factors on Children’s Compliance with Age-Based Nutritional Norms: An Experimental Study Using the Dish-I-Wish Web Application.’ The work has been carried out as part of the HSE Basic Research Programme and was presented at the XXVI April International Academic Conference named after Evgeny Yasin.
April 30, 2026
New Foresight Centre Study Identifies the Most Destructive Global Trends for Humankind
A team of researchers from the HSE International Research and Educational Foresight Centre has examined how global trends affect the quality of human life—from life expectancy to professional fulfilment. The findings of the study titled ‘Human Capital Transformation under the Influence of Global Trends’ were published in Foresight.
April 28, 2026
Scientists Develop Algorithm for Accurate Financial Time Series Forecasting
Researchers at the HSE Faculty of Computer Science benchmarked more than 200,000 model configurations for predicting financial asset prices and realised volatility, showing that performance can be improved by filtering out noise at specific frequencies in advance. This technique increased accuracy in 65% of cases. The authors also developed their own algorithm, which achieves accuracy comparable to that of the best models while requiring less computational power. The study has been published in Applied Soft Computing.

 

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Multimodal Clustering of Boolean Tensors on MapReduce: Experiments Revisited

P. 137–151.
Ignatov D. I., Egurnov D., Точилкин Д. С.

This paper presents further development of distributed multimodal clustering. We introduce a new version of multimodal clustering algorithm for distributed processing in Apache Hadoop on computer clusters. Its implementation allows a user to conduct clustering on data with modality greater than two. We provide time and space complexity of the algorithm and justify its relevance. The algorithm is adapted for MapReduce distributed processing model. The program implemented by means of Apache Hadoop framework is able to perform parallel computing on thousands of nodes.

Language: English
Full text
Text on another site
Keywords: анализ формальных понятийdata miningтриадический анализ формальных понятийFCA (Formal Concept Analysis)большие данныеbig dataмайнинг данныхMap ReduceTriadic Formal Concept AnalysisBoolean TensorsБулевы тензорыMap Reduce
Publication based on the results of:
Discovering and Representing Knowledge for Recommender Systems (2019)

In book

Supplementary Proceedings ICFCA 2019 Conference and Workshops
Vol. 2378. , CEUR Workshop Proceedings, 2019.
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