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Triclusters of Close Values for the Analysis of 3D Data
Automation and Remote Control. 2022. Vol. 83. No. 6. P. 894–902.
Egurnov D., Ignatov D. I.
Abstract: The paper deals with the problem of triclustering in multivalued triadic contexts in termsof one multidimensional extension of formal concept analysis; triclustering can be viewed as asearch for dense subtensors in three-dimensional tensors over the field of real numbers. Twomethods are proposed for solving this problem, namely, NOAC—a version of the OACtriclustering method for numerical data based on delta operators—and a triadic version ofthek-means method with an improved metric based on Manhattan distance andproximity predicates in each of the three dimensions. Numerical experiments are carried out bothon real and synthetic data and confirm the superiority of the NOAC method in terms of theperformance criteria for the resulting triclusters. © 2022, Pleiades Publishing, Ltd.
Strube M., Braud C., Hardmeier C. et al., Suzhou: Association for Computational Linguistics, 2025.
Added: June 11, 2026
Kh. Kh. Abdullin, D. B. Mokeev, D. S. Taletskii, Mathematical notes 2026 Vol. 119 No. 1 P. 3–7
By the Ramsey number R(K1,s,Pt) one means the least positive integer n such that, for every n-vertex graph G, the following condition holds: either G contains a vertex of degree at least s or the complement of G contains a simple t-path. In this paper, we fi nd precise values of R(K1,s,Pt) for certain values ...
Added: June 10, 2026
Sorokin D., Kostin A., Savchenko L. et al., Knowledge-Based Systems 2026 Vol. 348 Article 116258
A convenient approach to optimally solving combinatorial optimization tasks is the Branch-and-Bound method.
Its branching heuristic can be learned to solve a large set of similar tasks. The promising results here are
achieved by the recently appeared on-policy reinforcement learning method based on the tree Markov Decision
Process. To overcome its main disadvantages, namely, very large training time ...
Added: June 10, 2026
Namsaraev Z., Kozlova A., Toshchakov S., Scientific Reports 2026 Vol. 16 No. 17769
Distilled fermented milk beverages are rare in food technology, despite the global prevalence of plant-based spirits. Currently, the production of distilled strong alcoholic beverages from fermented milk using traditional technologies is known only among Mongolic-speaking peoples and their Siberian neighbors. This study provides the first interdisciplinary analysis of darasun, a traditional Buryat spirit made from fermented ...
Added: June 10, 2026
Hushchyn M., Butorova A., Bobakov V. et al., European Physical Journal: Special Topics 2026 P. 1–19
This paper presents a review of artificial intelligence (AI) methods for failure prediction in data center cooling systems, with a focus on the integration of digital twins (DTs), physics-informed learning, and graph-based models. Positioned within complex network science, this review addresses a limitation of conventional graph approaches—their reliance on pairwise connectivity—whereas real-world failures often arise ...
Added: June 10, 2026
Springer, 2026.
The book presents the proceedings of the 13th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2024), held at Intelligent Systems Research Group (ISRG), London Metropolitan University, London, United Kingdom, during June 6–7, 2025. Researchers, scientists, engineers and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with ...
Added: June 8, 2026
Flamarion M. V., Pelinovsky E., Nonlinear Dynamics 2026 Vol. 114 Article 784
In this article, we investigate wave packet and solitary wave dynamics in the Whitham–Ostrovsky (WO) equation. By means of a multiple-scales expansion, we formally derive a nonlinear Schrödinger (NLS) equation governing the envelope evolution.The corresponding modulational stability diagram is then obtained using the Lighthill criterion. We show that sufficiently large values of the low-frequency dispersive term render ...
Added: June 5, 2026
Ignatov D. I., , in: 11th International Conference, AIST 2023, Yerevan, Armenia, September 28–30, 2023, Revised Selected Papers. Analysis of Images, Social Networks and Texts. Lecture Notes in Computer Science (LNCS, volume 14486).: Cham: Springer, 2024. P. 349 – 361.
This paper dates back to the asymptotic solutions of Rota’s problem on the size of maximum antichain in the set partition lattice by Canfield and Harper and others. The knowledge of asymptotic coefficients could pave the way to the asymptotic solutions of such problems as (maximal) antichain counting in partition lattices. In addition to our ...
Added: January 23, 2026
Ignatov D. I., Khvorykh G., Khrunin A. et al., , in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary ProceedingsVol. 12602.: Springer, 2021. P. 185–204.
© 2021, Springer Nature Switzerland AG.Missing genotypes can affect the efficacy of machine learning approaches to identify the risk genetic variants of common diseases and traits. The problem occurs when genotypic data are collected from different experiments with different DNA microarrays, each being characterised by its pattern of uncalled (missing) genotypes. This can prevent the ...
Added: November 1, 2022
CEUR-WS.org, 2020.
The CLA conference is an international forum for researchers, practitioners and students dedicated to the practice of Formal Concept Analysis (FCA) and areas closely related to it, including data analysis and mining, information retrieval, knowledge management, knowledge engineering, logic, algebra and lattice theory.
The 15th of CLA, CLA 2020, was going to be held in Tallinn, Estonia ...
Added: October 30, 2020
CEUR Workshop Proceedings, 2018.
Added: November 25, 2018
Ignatov D. I., Semenov A., Комиссарова Д. В. et al., , in: Formal Concept Analysis of Social Networks.: Springer, 2017. Ch. 4 P. 59–96.
Multimodal clustering is an unsupervised technique for mining interesting patterns in n-ary relations or n-mode networks. Among different types of such generalised patterns one can find biclusters and formal concepts (maximal bicliques) for two-mode case, triclusters and triconcepts for three-mode case, closed n-sets for n-mode case, etc. Object-attribute biclustering (OA-biclustering) for mining large binary datatables (formal contexts or two-mode ...
Added: December 17, 2017
Egurnov D., Ignatov D. I., MEPHU NGUIFO E., , in: 23rd International Symposium on Methodologies for Intelligent Systems - Proceedings.: Birkhauser/Springer, 2017. P. 573–579.
Analysis of polyadic data (for example n-ary relations) becomes a popular task nowadays. While several data mining techniques exist for dyadic contexts, their extensions to triadic case are not obvious. In this work, we study development of ideas of Formal Concept Analysis for processing three-dimensional data, namely OAC-triclustering (from Object, Attribute, Condition). We consider several similar ...
Added: September 18, 2017
Masyutin A., Kashnitsky Y., , in: Foundations of Intelligent Systems.: Warsz.: Springer, 2017. P. 664–673.
The cornerstone of retail banking risk management is the estimation of the expected losses when granting a loan to the borrower. The key driver for loss estimation is probability of default (PD) of the borrower. Assessing PD lies in the area of classification problem. In this paper we apply FCA query-based classification techniques to Kaggle ...
Added: July 6, 2017
Egurnov D., Ignatov D. I., MEPHU NGUIFO E., , in: 14th International Conference on Formal Concept Analysis - Supplementary Proceedings.: University Rennes 1, 2017. P. 31–47.
Analysis of polyadic data (for example, multi-way tensors and n-ary relations) becomes more and more popular task nowadays. While several datamining techniques exist for (numeric) dyadic contexts, their extensions to the triadic case are not obvious, if possible at all. In this work, we study development of the ideas of Formal Concept Analysis for processing ...
Added: June 21, 2017
University Rennes 1, 2017.
This volume is the supplementary volume of the 14th International Conference on Formal Concept Analysis (ICFCA 2017), held from June 13th to 16th 2017, at IRISA, Rennes. The ICFCA conference series is one of the major venues for researches from the field of Formal Concept Analysis and related areas to present and discuss their recent ...
Added: June 19, 2017
Mirkin B., , in: CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop ProceedingsVol. 1624.: M.: Higher School of Economics, National Research University, 2016. P. 7–8.
Аpproximate cluster structures are those of formal concepts and n-concepts with added numerical intensity weights. The talk presents theoretical results and computational methods for approximate clustering and n-clustering as extensions of the algebraic-geometrical properties of numerical matrices (SVD and the like) to the situations where one or most of elements of the solutions to be ...
Added: March 3, 2017
Babin M. A., Kuznetsov S., Theoretical Computer Science 2017 Vol. Volume 658, Part B No. 7 January P. 316–326
Dualization of a monotone Boolean function on a finite lattice can be represented by transforming the set of its minimal 1 values to the set of its maximal 0 values. In this paper we consider finite lattices given by ordered sets of their meet and join irreducibles (i.e., as a concept lattice of a formal ...
Added: February 9, 2017
Бочаров А. А., Gnatyshak D. V., Ignatov D. I. et al., , in: CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop ProceedingsVol. 1624.: M.: Higher School of Economics, National Research University, 2016. P. 45–56.
We propose a new algorithm for consensus clustering, FCA-Consensus, based on Formal Concept Analysis. As the input, the algorithm takes T partitions of a certain set of objects obtained by k-means algorithm after T runs from different initialisations. The resulting consensus partition is extracted from an antichain of the concept lattice built on a formal ...
Added: October 24, 2016
Kuznetsov S., Makhalova T., , in: CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop ProceedingsVol. 1624.: M.: Higher School of Economics, National Research University, 2016. P. 245–253.
Triadic concept analysis has become a popular research direction, since triadic relations give natural models of many data collections. In this paper we address the problem of selecting most interesting concepts by proposing triadic stability indices ...
Added: October 11, 2016
Kashnitsky Y., Kuznetsov S., , in: Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 2016).: M.: [б.и.], 2016. P. 105–112.
Decision tree learning is one of the most popular classifica- tion techniques. However, by its nature it is a greedy approach to finding a classification hypothesis that optimizes some information-based crite- rion. It is very fast but may lead to finding suboptimal classification hy- potheses. Moreover, in spite of decision trees being easily interpretable, ensembles ...
Added: October 6, 2016
M.: [б.и.], 2016.
The four preceding editions of the FCA4AI Workshop showed that many researchers working in Artificial Intelligence are deeply interested by a well-founded method for classi- fication and mining such as Formal Concept Analysis (see http://www.fca4ai.hse.ru/). The first edition of FCA4AI was co-located with ECAI 2012 in Montpellier, the second one with IJCAI 2013 in Beijing, ...
Added: October 6, 2016
Kashnitsky Y., Kuznetsov S., , in: CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop ProceedingsVol. 1624.: M.: Higher School of Economics, National Research University, 2016. Ch. 19 P. 189–202.
Nowadays decision tree learning is one of the most popular classification and regression techniques. Though decision trees are not accurate on their own, they make very good base learners for advanced tree-based methods such as random forests and gradient boosted trees. However, applying ensembles of trees deteriorates interpretability of the final model. Another problem is ...
Added: October 6, 2016