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News
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Proceedings of the 21st International Symposium on String Processing and Information Retrieval

Springer, 2014.
Academic editor: M. Crochemore, E. Silva De Moura

This book constitutes the proceedings of the 21st International Symposium on String Processing and Information Retrieval, SPIRE 2014, held in Ouro Preto, Brazil, in October 2014. The 20 full and 6 short papers included in this volume were carefully reviewed and selected from 45 submissions. The papers focus not only on fundamental algorithms in string processing and information retrieval, but address also application areas such as computational biology, Web mining and recommender systems. They are organized in topical sections on compression, indexing, genome and related topics, sequences and strings, search, as well as on mining and recommending.

Chapters
Simple and Efficient String Algorithms for Query Suggestion Metrics Computation
Loptev A., Selugina A., Starikovskaya T., , in: Proceedings of the 21st International Symposium on String Processing and Information Retrieval.: Springer, 2014. P. 268–278.
In order to make query suggestion mechanisms more efficient, it is important to have metrics that will estimate query suggestions quality well. Recently, Kharitonov et al.~\cite{SuggestEvalKharitonov} proposed a family of metrics that showed much better alignment with user satisfaction than previously known metrics. However, they did not address the problem of computing the proposed metrics. ...
Added: October 4, 2014
Priority areas: IT and mathematics mathematics
Language: English
Keywords: data structuresAlgortihms
Proceedings of the 21st International Symposium on String Processing and Information Retrieval
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