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October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.
October 5, 2026
‘The Climate Transition Is Not Necessarily a Limitation for Business
Linara Khadimullina works in the field of low-carbon development. In an interview with the Young Scientists of HSE project, she spoke about why nature is not just a beautiful backdrop, her research on the role of sustainable corporate governance in reducing greenhouse gas emissions, and growing plants as a source of inspiration.
October 5, 2026
Africa, Youth, and Civic Dialogue: Public Diplomacy Discussed at HSE University
In late September, HSE University hosted a roundtable discussion titled Civil Society in African Countries and Youth Participation in Public Diplomacy. Representatives of non-governmental organisations from Ghana, Ethiopia, and Russia, along with students from HSE University’s Bachelor’s Programme in Public Administration, discussed how young people without official diplomatic status can influence relations between countries and how the nonprofit sector can remain sustainable amid declining grant funding.

 

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Complex Data Analytics with Formal Concept Analysis

Springer, 2022.
Academic editor: R. Missaoui, L. Kwuida, T. Abdessalem

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 lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and association rule mining.

 

Complex data analytics refers to advanced methods and tools for mining and analyzing data with complex structures such as XML/Json data, text and image data, multidimensional data, graphs, sequences and streaming data. It also covers visualization mechanisms used to highlight the discovered knowledge.

This edited book examines a set of important and relevant research directions in complex data management, and updates the  contribution of the FCA community in analyzing complex and large data such as knowledge graphs and interlinked contexts.  For example, Formal Concept Analysis and some of its extensions are exploited, revisited and coupled with recent processing parallel and distributed paradigms to maximize the benefits in analyzing large data.

Chapters
Triclustering in Big Data Setting
Egurnov D., Точилкин Д. С., Ignatov D. I., , in: Complex Data Analytics with Formal Concept Analysis.: Springer, 2022. P. 239–258.
In this paper, we describe versions of triclustering algorithms adapted for efficient calculations in distributed environments with MapReduce model or parallelisation mechanism provided by modern programming languages. OAC-family of triclustering algorithms shows good parallelisation capabilities due to the independent processing of triples of a triadic formal context. We provide time and space complexity of the ...
Added: November 1, 2022
Research target: Computer Science Mathematics
Language: English
Sample Chapter
DOI
Text on another site
Keywords: FCA (Formal Concept Analysis)artificial intelligencebig data analytics
Complex Data Analytics with Formal Concept Analysis
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