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News
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.

 

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Proceedings of the Workshop Formal Concept Analysis Meets Information Retrieval

Vol. 977. M. : CEUR Workshop Proceedings, 2013.
Editor-in-chief: Kuznetsov S., C. Carpineto, A. Napoli
Chapters
FCA-based Search for Duplicate Objects in Ontologies
Ilvovsky D., Klimushkin M. A., , in: Proceedings of the Workshop Formal Concept Analysis Meets Information RetrievalVol. 977.: M.: CEUR Workshop Proceedings, 2013. P. 44–54.
A new approach for detecting duplicates in ontology built on real redundant data is considered. This approach is based on transforma- tion of initial ontology into a formal context and processing this context using methods of Formal Concept Analysis (FCA). As a part of a new method we also introduce a new index for measuring ...
Added: November 19, 2013
Improving Text Retrieval Efficiency with Pattern Structures on Parse Thickets
Kuznetsov S., Strok F. V., Ilvovsky D. et al., , in: Proceedings of the Workshop Formal Concept Analysis Meets Information RetrievalVol. 977.: M.: CEUR Workshop Proceedings, 2013. P. 6–21.
We develop a graph representation and learning technique for parse  structures for paragraphs of text. We introduce Parse Thicket (PT) as a sum of  syntactic parse trees augmented by a number of arcs for inter-sentence word-word relations such as co-reference and taxonomic relations. These arcs are also derived from other sources, including Speech Act and ...
Added: November 18, 2013
Information Retrieval and Knowledge Discovery with FCART
Kuznetsov S., Neznanov A., , in: Proceedings of the Workshop Formal Concept Analysis Meets Information RetrievalVol. 977.: M.: CEUR Workshop Proceedings, 2013. P. 74–82.
We describe FCART software system, a universal integrated environment for knowledge and data engineers with a set of research tools based on  Formal Concept Analysis. The system is intended for knowledge discovery from big dynamic data collections, including text collections. FCART allows the user to load structured and unstructured data (texts and various metainformation) from ...
Added: November 18, 2013
Priority areas: IT and mathematics
Language: English
Full text
Keywords: information retrievalFCA (Formal Concept Analysis)
Proceedings of the Workshop Formal Concept Analysis Meets Information Retrieval
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Added: October 4, 2023
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Dudyrev E., Kuznetsov S., Napoli A., , in: 17th International Conference, ICFCA 2023, Kassel, Germany, July 17–21, 2023, Proceedings. Formal Concept Analysis, (LNCS, volume 13934).: Switzerland: Springer, 2023. P. 127–142.
In this paper we introduce and study description quivers as compact representations of concept lattices and respective ensembles of decision trees. Formally, description quivers are directed multigraphs where vertices represent concept intents and (multiple) edges represent generators of intents. We study some properties of description quivers and shed light on their use for describing state-of-the-art symbolic machine ...
Added: October 4, 2023
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Egurnov D., Точилкин Д. С., Ignatov D. I., , in: Complex Data Analytics with Formal Concept Analysis.: Springer, 2022. P. 239–258.
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Complex Data Analytics with Formal Concept Analysis
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FCA is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. Its mathematical power comes from its concept ...
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Galitsky B., Ilvovsky D., Goncharova E., , in: Proceedings of the 10th International Workshop "What can FCA do for Artificial Intelligence?"Vol. 3233.: CEUR Workshop Proceedings, 2022. P. 75–87.
Supported decision trees that have been first proposed to boost the performance and the explainability of the expert systems built upon the texts can become a great basis for the machine reading comprehension (MRC) systems. The supported decision tree is based on building and combining the corresponding discourse trees for the text passage. In this work, ...
Added: November 1, 2022
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