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Learning Implications from Data and from Queries
P. 32–44.
Obiedkov S.
In this paper, we consider computational problems related to finding implications in an explicitly given formal context or via queries to an oracle. We are concerned with two types of problems: enumerating implications (or association rules) and finding a single implication satisfying certain conditions. We present complexity results for some of these problems and leave others open. The paper is not meant as a comprehensive survey, but rather as a subjective selection of interesting problems.
Junyu B., Fei H., Huilin F. et al., International Journal of Approximate Reasoning 2025 Vol. 187 Article 109541
In Formal Concept Analysis (FCA), concept reduction serves as an important means of simplification. The application scenarios of concept reduction cover various aspects such as data mining, knowledge discovery, strategic decision-making, and rule learning. For symmetric formal contexts, a specialized class of concept reduction exists that can fully recover all knowledge. However, most existing concept ...
Added: December 1, 2025
Dudyrev E., Mariia Zueva, Kuznetsov S. et al., , in: FCA4AI 2024: The 12th International Workshop "What can FCA do for Artificial Intelligence?", October 19 2024, Santiago de Compostela, SpainVol. 3911.: CEUR Workshop Proceedings, 2024. P. 47–58.
Clustering aims at finding disjoint groups of similar objects in data and is one major task in Machine Learning. It is also gaining more attention in Formal Concept Analysis community in these last years. This paper proposes an original approach to the clustering of complex data based on Formal Concept Analysis (FCA) and Pattern Structures. ...
Added: April 30, 2025
CEUR Workshop Proceedings, 2024.
The eleven preceding editions of the FCA4AI Workshop showed that many researchers working in Articial Intelligence are deeply interested in a well-founded method for classication and data mining such as Formal Concept Analysis (see https://upriss.github.io/fca/fca.html).
The FCA4AI Workshop Series started with ECAI 2012 (Montpellier) and the last edition was co-located with IJCAI 2023 (Macao, China). The ...
Added: April 29, 2025
Kanaev E., Garaeva A., Fedorenko D. O., , in: Cooperation in Asia-Pacific: Transition to a New World Order.: M.: IOS RAS, 2025. P. 8–10.
The chapter discusses the implications of the US-China technological rivalry for ASEAN and its digital projects. ...
Added: April 5, 2025
Ермаков С. Р., Zykov S. V., Научно-технический вестник Поволжья 2025 № 2 С. 118–122
В данной научной работе авторами предлагается метод масштабирования признаков для потоковой интеллектуальной образовательной системы. Описано функционирование метода и приведена схема. Проведено экспериментальное исследование метода, результаты которого отражены в виде графика. Полученные выводы подтверждают эффективность предложенного метода по сравнению с рассмотренными аналогами. ...
Added: March 14, 2025
Dudyrev E., Kuznetsov S., Napoli A., , in: FCA4AI 2023 What can FCA do for Artificial Intelligence 2023 Proceedings of the 11th International Workshop "What can FCA do for Artificial Intelligence?" co-located with the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023) Macao, S.A.R. China; August 20, 2023Vol. 3489.: CEUR-WS.org, 2023. P. 69–80.
Rule Learning and Formal Concept Analysis (FCA) are two fields of science that study similar topic yet speak in a very different terms. This paper describes rule-based machine learning models with FCA-based terminology which results in decision quiver model. A decision quiver, discussed in the paper, is a supervised machine learning model that is based ...
Added: October 4, 2023
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
Kanaev E., Luzyanin S., , in: The global reset: insights from regions.: M.: Advanced Solutions, 2022. P. 4–11.
The chapter points out salient features of the present-day globalization and outlines major changes that have been generated by the policies of Asia-Pacific economic actors. ...
Added: June 11, 2023
Kanaev E., Terskikh M., , in: The global reset: insights from regions.: M.: Advanced Solutions, 2022.
The chapter analyses Russia’s position on the Indo-Pacifi c region, its perception in the Russian expert and political communities, as well as its impact on Russia’s interests. The paper offers insights into Russia’s expert assessments of the Indo-Pacifi c region, presents mainstream points of view from a political and security perspective. The authors trace Russia’s ...
Added: June 11, 2023
terskikh M., , in: The global reset: insights from regions.: M.: Advanced Solutions, 2022. P. 88–97.
The chapter analyses Russia’s position on the Indo-Pacifi c region, its perception in the Russian expert and political communities, as well as its impact on Russia’s interests. The paper offers insights into Russia’s expert assessments of the Indo-Pacifi c region, presents mainstream points of view from a political and security perspective. The authors trace Russia’s ...
Added: June 11, 2023
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
Springer, 2022.
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 ...
Added: November 1, 2022
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
Dudyrev E., Kuznetsov S., , in: Proceedings of the 10th International Workshop "What can FCA do for Artificial Intelligence?"Vol. 3233.: CEUR Workshop Proceedings, 2022. P. 23–34.
Studies on Explainable Artificial Intelligence show that a model should be small in order to be human understandable. The restriction on the size of a model drastically reduces the space of possible solutions. Many rule learning models still rely on greedy algorithms for generating ensembles of decision trees. This paper discusses FCA-inspired mathematical and engineering ...
Added: November 1, 2022
Dudyrev E., Kuznetsov S., , in: Proceedings of the 9th International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2021)Vol. 2972.: CEUR-WS, 2021. Ch. 9 P. 99–104.
Ensembles of decision trees, like Random Forests are efficient machine learning models with state-of-the-art prediction quality. However, their predictions are much less transparent than those of a single decision tree. In this paper, we describe a prediction model based on a single decision tree in terms of Formal Concept Analysis. We define a differential way ...
Added: December 8, 2021
Buzmakov A. V., Kuznetsov S., Makhalova T. et al., , in: Proceedings of the 9th International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2021)Vol. 2972.: CEUR-WS, 2021. Ch. 2 P. 19–26.
Added: December 7, 2021
Goncharova E., Ilvovsky D., Galitsky B., , in: Proceedings of the 9th International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2021)Vol. 2972.: CEUR-WS, 2021. P. 51–58.
Added: October 28, 2021
Springer, 2021.
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 ...
Added: July 10, 2021
Марченко Е. Ю., Suschevskiy V., , in: Proceedings of the 22nd International Academic Mindtrek Conference.: NY: ACM, 2018. P. 255–257.
In this work, we analyze how the esports transfer market is organized with the help of mixed methods. We assume that a combination of Social Network Analysis and Machine Learning can help to achieve deeper understanding and to find patterns which are hidden from the one-side analysis. For the research, we gathered information about transfers ...
Added: April 17, 2021
Belfodil A., Kuznetsov S., Kaytoue M., International Journal of General Systems 2020 Vol. 49 No. 8 P. 785–818
Order and lattice theory provides convenient mathematical tools for pattern mining, in particular for condensed irredundant representations of pattern spaces and their efficient generation. Formal Concept Analysis (FCA) offers a generic framework, called pattern structures, to formalize many types of patterns, such as itemsets, intervals, graphs, and sequence sets. Moreover, FCA provides generic algorithms to generate irredundantly all ...
Added: January 25, 2021
Yarullin R., Obiedkov S., International Journal of Approximate Reasoning 2020 Vol. 127 P. 1–16
In Angluin's exact-learning framework, equivalence queries can be simulated by stochastic equivalence testing to achieve a probably approximately correct identification of an unknown concept. We present an analysis of the number of samples that need to be generated in the process leading to a theoretical improvement on an earlier approach. We apply this modification to ...
Added: October 6, 2020
Makhalova T., Ilvovsky D., Galitsky B. et al., , in: RAAI 2020 Russian Advances in Artificial Intelligence 2020 Selected Contributions of the "Russian Advances in Artificial Intelligence" Track at RCAI 2020 co-located with 18th Russian Conference on Artificial Intelligence (RCAI 2020)Vol. 2648.: CEUR-WS, 2020. P. 144–156.
Information retrieval (IR) chatbot is a special class of virtual assistants, which is widely used nowadays in customer support services. However, the work of modern IR retrieval systems is limited by simple queries to the database, which does not utilize all the potential of interaction with the user. In this paper we implement an FCA-based ...
Added: September 15, 2020