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Vol. 1624. , M.: Higher School of Economics, National Research University, 2016.
Игнатов Д. И., , 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.
Добавлено: 23 января 2026 г.
Kemgne M. W., Njionou B. B., Игнатов Д. И. и др., International Journal of Approximate Reasoning 2025 Vol. 186 Article 109527
Добавлено: 23 января 2026 г.
Stepan L. Kuznetsov, Journal of Logic and Computation 2026 Vol. 36 No. 1 Article exaf078
Добавлено: 14 января 2026 г.
Stepan L. Kuznetsov, , in: Logic, Language, Information, and Computation: 30th International Workshop, WoLLIC 2024, Bern, Switzerland, June 10–13, 2024, ProceedingsVol. 14672: Lecture Notes in Computer Science.: Cham: Springer, 2024. P. 93–107.
Добавлено: 12 июня 2024 г.
Игнатов Д. И., , in: LNAI 14133: 28th International Conference on Conceptual Structures, ICCS 2023, Berlin, Germany, September 11–13, 2023, Proceedings. Graph-Based Representation and Reasoning.: Berlin: Springer, 2023. P. 56–69.
Добавлено: 23 ноября 2023 г.
Дудырев Е. О., Кузнецов С. О., , in: Formal Concept Analysis: 16th International Conference, ICFCA 2021, Strasbourg, France, June 29 – July 2, 2021, Proceedings.: Springer, 2021. Ch. 16 P. 252–260.
Добавлено: 28 сентября 2021 г.
Springer, 2021.
Книга вклюает в себя работы 16ой международной конференции по Анализу формальных понятий. Книга поделена на 5 секций: теория, правила, методы и приложения, исследование и визуализация ...
Добавлено: 10 июля 2021 г.
CEUR-WS.org, 2020.
Добавлено: 30 октября 2020 г.
CEUR-WS, 2020.
Добавлено: 29 октября 2020 г.
Кузнецов С. О., Demko C., Bertet K. и др., , in: Electronic Procedings Theoretical Computer ScienceVol. 845.: [б.и.], 2020. P. 1–20.
Добавлено: 29 октября 2020 г.
CEUR Workshop Proceedings, 2019.
Добавлено: 31 октября 2019 г.
Birkhauser/Springer, 2017.
Добавлено: 18 сентября 2017 г.
Бочаров А. А., Гнатышак Д. В., Игнатов Д. И. и др., , 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.
Добавлено: 24 октября 2016 г.
M.: Higher School of Economics, National Research University, 2016.
The 13th International Conference on “Concept Lattices and Applications (CLA 2016)” was held at National Research University Higher School of Economics, Moscow, Russia from July 18 until July 22, 2016. The CLA conference, organized since 2002, aims to provide to everyone interested in Formal Concept Analysis and more generally in Concept Lattices or Galois Lattices, ...
Добавлено: 6 октября 2016 г.
Bernhard Ganter, Объедков С. А., Berlin, Heidelberg: Springer, 2016.
This is the first textbook on attribute exploration, its theory, its algorithms for applications, and some of its many possible generalizations. Attribute exploration is useful for acquiring structured knowledge through an interactive process, by asking queries to an expert. Generalizations that handle incomplete, faulty, or imprecise data are discussed, but the focus lies on knowledge ...
Добавлено: 3 сентября 2016 г.
Игнатов Д. И., Watson B., , in: RuZA 2015 Workshop. Proceedings of Russian and South African Workshop on Knowledge Discovery Techniques Based on Formal Concept Analysis (RuZA 2015). November 30 - December 5, 2015, Stellenbosch, South AfricaVol. 1552.: Aachen: CEUR Workshop Proceedings, 2015.
Being an unsupervised machine learning and data mining technique, biclustering and its multimodal extensions are becoming popular tools for analysing object-attribute data in different domains. Apart from conventional clustering techniques, biclustering is searching for homogeneous groups of objects while keeping their common description, e.g., in binary setting, their shared attributes. In bioinformatics, biclustering is used ...
Добавлено: 14 июня 2016 г.
Clermont-Ferrand: CEUR Workshop Proceedings, 2015.
Formal Concept Analysis is a method of analysis of logical data based on formalization of conceptual knowledge by means of lattice theory. It has proved to be of interest to various applied fields such as data visualization, knowledge discovery and data mining, database theory, and many others. The International Conference “Concept Lattices and Their Applications ...
Добавлено: 22 октября 2015 г.
Kosice: Pavol Jozef Safarik University, 2014.
Formal Concept Analysis is a mathematical theory formalizing aspects of human conceptual thinking by means of lattice theory. As such, it constitutes a theoretically well-founded, practically proven, human-centered approach to data science and has been continuously contributing valuable insights, methodologies and algorithms to the scientic community. The International Conference "Concept Lattices and Their Applications (CLA)" ...
Добавлено: 8 октября 2014 г.
La Rochelle: Laboratory L3i, University of La Rochelle, 2013.
Добавлено: 18 октября 2013 г.
Кузнецов С. О., Poelman J., Elzinga P. и др., Lecture Notes in Computer Science 2012 Vol. 7377 LNAI P. 528–272
In this paper we introduce a novel human-centered data mining software system which was designed to gain intelligence from unstructured textual data. The architecture takes its roots in several case studies which were a collaboration between the Amsterdam-Amstelland Police, GasthuisZusters Antwerpen (GZA) hospitals and KU Leuven. It is currently being implemented by bachelor and master ...
Добавлено: 7 февраля 2013 г.