Formal Concept Analysis: 16th International Conference, ICFCA 2021, Strasbourg, France, June 29 – July 2, 2021, Proceedings

doi:10.1007/978-3-030-77867-5

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Formal Concept Analysis: 16th International Conference, ICFCA 2021, Strasbourg, France, June 29 – July 2, 2021, Proceedings

Springer, 2021.

Academic editor: A. Braud, Buzmakov Aleksey, T. Hanika, F. Le Ber

This book constitutes the proceedings of the 16th International Conference on Formal Concept Analysis, ICFCA 2021, held in Strasbourg, France, in June/July 2021.

The 14 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 32 submissions. The book also contains four invited contributions in full paper length.

The research part of this volume is divided in five different sections. First, "Theory" contains compiled works that discuss advances on theoretical aspects of FCA. Second, the section "Rules" consists of contributions devoted to implications and association rules. The third section "Methods and Applications" is composed of results that are concerned with new algorithms and their applications. "Exploration and Visualization" introduces different approaches to data exploration.

Approximate Computation of Exact Association Rules

Bansal S., Kailasam S., Obiedkov S., , in: Formal Concept Analysis: 16th International Conference, ICFCA 2021, Strasbourg, France, June 29 – July 2, 2021, Proceedings.: Springer, 2021. P. 107–122.

We adapt a polynomial-time approximation algorithm for computing the canonical basis of implications to approximately compute frequent implications, also known as exact association rules. To this end, we define a suitable notion of approximation that takes into account the frequency of attribute subsets and show that our algorithm achieves a desired approximation with high probability. ...

Added: December 9, 2021

Decision Concept Lattice vs. Decision Trees and Random Forests

Dudyrev E., Kuznetsov S., , in: Formal Concept Analysis: 16th International Conference, ICFCA 2021, Strasbourg, France, June 29 – July 2, 2021, Proceedings.: Springer, 2021. Ch. 16 P. 252–260.

Added: September 28, 2021

Research target: Mathematics Computer Science

Priority areas: IT and mathematics

Structural model of decision support system for sustainable development of oil and gas companies

Stoianova A. D., Trofimets V. Y., Matrokhina K. V., International Journal of Engineering, Transactions A: Basics 2025 Vol. 38 No. 4 P. 701–709

The article considers the issue of managerial decision-making in an oil and gas company, which is related to the class of multi-criteria choice problems. To improve the validity of decisions in the context of companies’ sustainable development it is proposed to implement a Decision Support System (DSS). A brief review of the existing methods of ...

Added: November 10, 2026

К теореме Гудмана-Штрауса

Vereshchagin N., Математический сборник 2026 Т. 217 № 10 С. 3–46

Теорема Гудмана-Штрауса утверждает, что для “почти всякой” подстановки семейство подстановочных замощений софично, т.е. может быть задано локальными правилами для некоторой раскраски плиток. Условия на подстановку, гарантирующие софичность, довольно сложные. В настоящей работе мы предлагаем версию теоремы Гудмана-Штрауса с более простыми условиями на подстановку. Хотя эти условия достаточно ограничительны, мы показываем, что в сочетании с двумя простыми приемами (взятием достаточно ...

Added: November 10, 2026

EdFitter: a hybrid course recommendation system using large language models

Sergei Koltcov, Ryumin D., Alexandr Axyonov et al., PeerJ Computer Science 2026 Article 12:e4141

Educational institutions face increasing pressure to adapt their curricula to the rapidly evolving demands of the job market, and recommender systems can be important tools to guide students in selecting courses that align with their career goals. We present EdFitter, a hybrid course recommendation system that combines pretrained text embeddings for retrieval with large language ...

Added: November 10, 2026

Assessing density equilibration in confined Liquid–Liquid interfaces

Guskov T., Gerke K., Kondratyuk N. et al., Molecular Simulation 2026 Vol. 52 No. 7 P. 546 – 555

Equilibration is often assumed rather than tested in molecular dynamics studies of confined liquid–liquid interfaces, even though different physical properties may relax on different time scales. In this work, equilibration is examined using an automated truncation method based on the marginal standard error rule. Interfacial geometry, wetting behaviour, and density-related properties are analysed for liquid–liquid ...

Added: November 10, 2026

Influence of nuclear quantum effects on metastable states of warm dense hydrogen

Lukyanchuk V., Norman G., Kondratyuk N. et al., Scientific Reports 2026 Vol. 16 No. 1 Article 16435

Previously, it has been effectively shown that nuclear quantum effects (NQE) considerably influence the prediction of the warm dense hydrogen phase diagram. Here, we study the influence of NQE on the parameters of the conducting state formation in warm dense hydrogen using path integral molecular dynamics (PIMD) within the framework of the finite temperature density ...

Added: November 10, 2026

Machine Learning and Knowledge Discovery in Databases. Research Track and Applied Data Science Track. European Conference, ECML PKDD 2026, Naples, Italy, September 7–11, 2026, Proceedings

Springer, 2027.

This volume is Part VIII of the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2026, held in Naples, Italy, September 7–11, 2026. It contains 40 papers from the Research Track and the Applied Data Science Track and is published as volume 16948 of Lecture Notes in ...

Added: November 9, 2026

Artificial Intelligence for Software Engineering (AI4SE): A Review of Capabilities, Evaluation, and Verification Challenges

Avdoshin S.M., Pesotskaya E.Y., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 6, part 2 P. 133–146

Artificial intelligence has significantly reshaped contemporary software engineering practice, changing how software systems are designed, implemented, tested, and maintained. Recent advances in large language models and AI-assisted development tools have expanded the role of AI from supporting isolated tasks to participating in multiple stages of the software lifecycle. In many development settings, software is now created from high-level specifications ...

Added: November 8, 2026

MFL-ScrollNet: Recurrent Sliding-Window Detection for Panoramic Pipeline Magnetic Flux Leakage Images

Aleksei Samarin, Belous F., Торопов А. Г. et al., Technologies 2026 Vol. 14 No. 11 P. 1–21

Abstract Automated interpretation of magnetic flux leakage (MFL) data is central to condition assessment of long-distance oil and gas pipelines. Yet, full-resolution panoramas are difficult to process without either suppressing small anomalies through resizing or fragmenting elongated objects at sliding-window boundaries. We propose MFL-ScrollNet, a recurrent sliding-window detector that formulates panoramic analysis as an ordered sequence ...

Added: November 8, 2026

Proceedings 2026 IEEE International Conference on Joint Cloud Computing JCC 2026

IEEE Computer Society (Conference Publishing Services, CPS), 2026.

Added: November 7, 2026

Detecting the undetectable: benchmarking AI-generated text

Sergey Avdoshin, Elena Pesotskaya, Saleh H. et al., Procedia Computer Science 2026 Vol. 292 P. 1332–1341

The rapid development of generative large language models (LLMs) has intensified the need for reliable methods capable of distinguishing AI-generated text from human writing, especially in academic and professional settings. This paper presents the results of a systematic benchmarking study evaluating the performance and limitations of contemporary LLM-text detectors applied to Russian-language academic content. We introduce ...

Added: November 7, 2026

PrimeKV: Preserving critical KV cache without attention scores for long-context inference

Zhang Z., Ilvovsky D., Neurocomputing 2027 Vol. 710

Efficient management of the Key-Value (KV) cache is essential for deploying large language models (LLMs) in long-context scenarios, where memory requirements often exceed the capacity of resource-constrained hardware. Many existing training-free compression algorithms typically rely on attention-driven heuristics, but exhibit two key limitations. First, they require explicit attention score computation, which is difficult to reconcile ...

Added: November 5, 2026

Обобщение матричной теоремы о деревьях для пар деревьев

Retinsky V., Функциональный анализ и его приложения 2026 Т. 60 № 4 С. 83–100

Приведено обобщение матричной теоремы о деревьях на случай перечисления пар остовных деревьев. Это обобщение включает в качестве частных случаев и унифицирует сразу несколько известных ранее результатов, в частности классическую теорему Кирхгофа, теорему Масбаума–Вайнтроба о перечислении 3-деревьев, а также аналог матричной теоремы о деревьях для перечисления 4-элементов Кирхгофа. ...

Added: November 5, 2026

Спаривания на алгебре рядов Лорана над кольцом

Levashev V., Математические заметки 2026 Т. 120 № 5 С. 843–846

Пусть 𝐴 – коммутативное ассоциативное кольцо с единицей и 𝐴((𝑡)) = 𝐴[[𝑡]][𝑡−1] – кольцо рядов Лорана над 𝐴. Алгебра 𝐴((𝑡)) имеет естественную топологию, где 𝐴 – подмодули вида 𝑡𝑚𝐴[[𝑡]] образуют базу окрестностей нуля. Пусть также Ω1𝐴((𝑡))/𝐴 – модуль кэлеровых 1-дифференциалов 𝐴((𝑡)) над 𝐴. ...

Added: November 5, 2026

Spectral structure of the mixed Hessian of the dispersionless Toda τ-function

Алексеев О. В., Letters in Mathematical Physics 2026 Vol. 116 No. 5 Article 132

We study the mixed Hessian of the dispersionless Toda \(\tau\)-function for the one-harmonic \(s\)-fold symmetric conformal map \(f(w)=r\bigl(w+\zeta w^{1-s}\bigr)\), where \(r>0\) is the exterior conformal radius and \(\zeta>0\) is the dimensionless shape parameter. This Hessian is the susceptibility matrix generated by the inverse conformal map. Our spectral statements are formulated for its weighted symmetry-block realizations ...

Added: November 5, 2026

A Multimodal Framework for Aphasia Severity Classification in Russian

Kolmogorova A., Ekaterina Yavshitz, Margolina A. et al., Association for Computational Linguistics, 2026.

Automatic classification of aphasia severity presents persistent challenges, particularly for languages with limited clinical speech re sources such as Russian. This paper explores a multimodal approach to severity estimation that combines acoustic and semantic representa tions of pathological speech. Acoustic features are extracted using pretrained Wav2Vec 2.0 models, while semantic information is obtained from the ...

Added: November 4, 2026

Modular Arrangements

Levin A., Sakharova N., / Series arXiv "math". 2024. No. 2412.17795.

The modular curves serve as excellent objects for testing conjectures in arithmetic geometry. They possess a natural geometric definition in contrast with rather nontrivial structure. On the other hand, they are well-studied from the perspective of number theory. Furthermore, there is a well-developed and powerful analytic technique available. We will use the square of the ...

Added: November 4, 2026

Interpretable GNN with Stable Concepts as Neurons

Kuznetsov S., CEUR Workshop Proceedings 2026 Vol. Vol-4247 P. 27–32

A method for constructing interpretable graph neural networks based on an ordered subsets of "interesting" formal concepts is proposed. Interestingness indices for selecting concepts are compared, namely frequency (extent size) and Δ-stability. The experimental results demonstrate that Δ-stability provides superior performance of the generated networks at the inference stage. ...

Added: November 2, 2026

Predicting multi-component oil viscosity using machine learning methods

Deshchenya V., Nikolay D. Kondratyuk, Sivakova A. et al., Chemical Engineering Sciences 2027 Vol. 337 Article 124616

Accurate prediction of complex formulation viscosity is crucial for the lubricant industry and engineering processes. However, developing generalizable models remains challenging due to the complexity of industrial mixtures and the scarcity of public experimental data, often resulting from corporate proprietary restrictions. This study presents a machine-learning workflow for viscosity estimation from a proprietary pseudonymized dataset, ...

Added: October 28, 2026

Parameterization and calibration of wild blueberry machine learning models to predict fruit-set in the northeast china bog blueberry agroecosystem

Qu H., Xiang R., Obsie E. Y. et al., Agronomy 2021

Data deficiency prevents the development of reliable machine learning models for many agroecosystems, especially those characterized by a dearth of knowledge derived from field data. However, other similar agroecosystems with extensive data resources can be of use. We propose a new predictive modeling approach based upon the concept of transfer learning to solve the problem ...

Added: October 22, 2026

Статистические методы анализа экономики и общества. 17-я Международная научно-практическая конференция студентов и аспирантов (12–15 мая 2026 г.)

М.: Издательский дом НИУ ВШЭ, 2026.

В сборнике представлены отобранные оргкомитетом труды участников 17-й Международной научно-практической конференции студентов и аспирантов «Статистические методы анализа экономики и общества» из России, Армении, Беларуси и Китая, представляющих 27 вузов из 16 городов: Москва, Владивосток, Ереван, Йошкар-Ола, Минск, Новосибирск, Оренбург, Ростов-на-Дону, Санкт-Петербург, Саранск, Саратов, Севастополь, Уфа, Шахты, Шэньчжэнь, Электросталь. Исследования посвящены вопросам статистической методологии, применению математико-статистических и ...

Added: October 21, 2026

On Calculation of Robustness and Stability of Formal Concepts Based on Delta Measure

Parkhomenko V., Kulikova S., Buzmakov A. V., Lobachevskii Journal of Mathematics 2026 Vol. 47 No. 6 P. 2979–2992

The stability of formal concepts and its generalization as robustness are considered in the paper. We use an approximation of stability in the form of Δ-measure for fast calculations. A computationally efficient method for calculating robustness based on subcontexts is presented. We also present a new method to analytically evaluate the number of preimages for ...

Added: October 14, 2026

Анализ алгоритмов квантовых вычислений в биомедицине

Gorbunov A. A., Григорьев А. А., Демидов Л. Н. et al., Приборы и системы. Управление, контроль, диагностика 2025 № 7 С. 20–24

Быстрое развитие технологии квантовых вычислений потенциально может произвести революцию в сложных вычислениях в физических, химических и биологических областях за счет использования квантовой суперпозиции и запутанности. Квантовые компьютеры используют кубиты, способные существовать в нескольких состояниях одновременно, в отличие от классических битов. Эта функция позволяет хранить и обрабатывать больше информации, что дает значительное преимущество при решении задач с обширным пространством ...

Added: October 12, 2026

Interpretability of Neural-Network Models for the Synthesis and Analysis of Microstrip Microwave Filters: Application of SHAP and LIME

Suslova A., Popova P., Arinin O. et al., , in: 2026 Systems of Signal Synchronization, Generating and Processing in Telecommunications, SYNCHROINFO 2026 (IEEE Conference # 70145), 30 June – 03 July, 2026.: IEEE Circuits and Systems Society, 2026. P. 1–4.

This paper investigates the interpretability of neuralnetwork models applied to the automated design of microstrip bandpass microwave filters. Two tasks are considered: the inverse task (synthesis of the filter geometry from a required frequency response) and the forward task (prediction of the magnitude–frequency response from the geometry). For both tasks a fully connected neural network is chosen as a single architecture ...

Added: October 3, 2026

Enhancing Boundary Stability in Decision Trees and Random Forests: A Weighted Sample Duplication Approach

Konstantinov A., Elizarova Anastasiya P., Utkin L., Computing, Telecommunications and Control 2026 Vol. 19 No. 1 P. 16–25

Decision trees and their ensemble extensions, such as random forests, are widely used as classification models due to their simplicity and interpretability. However, in many real-world tasks where class labels overlap in the feature space, standard decision trees rely on hard splits that create fragile decision boundaries. In these regions, small perturbations in the input ...

Added: October 2, 2026