Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017.. Val. 1921.

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Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017.

Vol. 1921. CEUR-WS.org, 2017.

Под общей редакцией: Кузнецов С. О., B. Watson

Pattern Structures for Risk Group Identification

Корепанова Н. В., Кузнецов С. О., , in: Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017.Vol. 1921.: CEUR-WS.org, 2017. P. 13–21.

Добавлено: 4 октября 2017 г.

An Incremental Algorithm for Computing n-concepts

Махалова Т. П., Nourine L., , in: Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017.Vol. 1921.: CEUR-WS.org, 2017.

Добавлено: 10 октября 2017 г.

Notes on relation between symbolic classifiers

Naidenova X., Бузмаков А. В., Parkhomenko V. и др., , in: Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017.Vol. 1921.: CEUR-WS.org, 2017. P. 88–103.

Добавлено: 14 марта 2018 г.

Analysis of Strong and Weak Ties in Oil & Gas Professional Community

Докука С. В., Яворский Р. Э., Krasnov F. и др., , in: Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017.Vol. 1921.: CEUR-WS.org, 2017. Ch. 3 P. 22–33.

The importance of weak social ties in professional commu- nities is well studied and widely accepted. In our paper we analyze the structure of strong ties based on the co-authorship relation and use the formal concept analysis framework to figure out weak ties. The research is motivated by fast growing need in cross-disciplinary research, which ...

Добавлено: 24 сентября 2018 г.

Язык: английский

Текст на другом сайте

Ключевые слова: Formal Concept Analysis Knowledge Discovery and Data Mining

Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017.

Is Canfield Right? On the Asymptotic Coefficients for the Maximum Antichain of Partitions and Related Counting Inequalities

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.

Object-Attribute Biclustering for Elimination of Missing Genotypes in Ischemic Stroke Genome-Wide Data

Игнатов Д. И., Khvorykh G., Khrunin A. и др., , 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.

Добавлено: 1 ноября 2022 г.

Triclusters of Close Values for the Analysis of 3D Data

Егурнов Д. А., Игнатов Д. И., Automation and Remote Control 2022 Vol. 83 No. 6 P. 894–902

Добавлено: 1 ноября 2022 г.

Proceedings of the Fifthteenth International Conference on Concept Lattices and Their Applications

CEUR-WS.org, 2020.

Добавлено: 30 октября 2020 г.

WIMS 2020: Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics

Association for Computing Machinery (ACM), 2020.

Добавлено: 28 августа 2020 г.

CLA 2018: The 14th International Conference on Concept Lattices and Their Applications

CEUR Workshop Proceedings, 2018.

Добавлено: 25 ноября 2018 г.

MDL for FCA: is there a place for background knowledge?

Кузнецов С. О., Махалова Т. П., Napoli A., , in: Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at IJCAI/ECAI 2018)Vol. 2149: CEUR Workshop Proceedings.: CEUR-WS, 2018.

Добавлено: 6 сентября 2018 г.

Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at IJCAI/ECAI 2018)

CEUR-WS, 2018.

Добавлено: 6 сентября 2018 г.

Multimodal Clustering for Community Detection

Игнатов Д. И., Семенов А. В., Комиссарова Д. В. и др., , in: Formal Concept Analysis of Social Networks.: Springer, 2017. Ch. 4 P. 59–96.

Добавлено: 17 декабря 2017 г.

Query-Based Versus Tree-Based Classification: Application to Banking Data

Масютин А. А., Кашницкий Ю. С., , 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 ...

Добавлено: 6 июля 2017 г.

14th International Conference on Formal Concept Analysis - Supplementary Proceedings

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 ...

Добавлено: 19 июня 2017 г.

Approximate clusters, biclusters and n-clusters in the analysis of binary and general data matrices

Миркин Б. Г., , 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 ...

Добавлено: 3 марта 2017 г.

Dualization in lattices given by ordered sets of irreducibles

Бабин М. А., Кузнецов С. О., 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 ...

Добавлено: 9 февраля 2017 г.

A Lattice-based Consensus Clustering Algorithm

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.

Building a Domain Knowledge Model based on a Concept Lattice Integrating Expert Constraints

Tang M. T., Бузмаков А. В., Toussaint Y. 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. 349–362.

Добавлено: 14 октября 2016 г.

On Stability of Triadic Concepts

Кузнецов С. О., Махалова Т. П., , 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.

Добавлено: 11 октября 2016 г.

Interval Pattern Concept Lattice as a Classifier Ensemble

Кашницкий Ю. С., Кузнецов С. О., , 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 ...

Добавлено: 6 октября 2016 г.

Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 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, ...

Добавлено: 6 октября 2016 г.

Global Optimization in Learning with Important Data: an FCA-Based Approach

Кашницкий Ю. С., Кузнецов С. О., , 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 ...

Добавлено: 6 октября 2016 г.

CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop Proceedings

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.

Lazy Learning of Succinct Classification Rules for Complex Structure Data

Кашницкий Ю. С., , in: Supplementary Proceedings of the 5th International Conference on Analysis of Images, Social Networks and Texts (AIST-SUP 2016), Yekaterinburg, Russia, April 7-9, 2016.Vol. 1710.: Aachen: CEUR Workshop Proceedings, 2016. Ch. 8 P. 73–84.

In this paper, we address machine learning classification problem and classify each test instance with a set of interpretable and accurate rules. We resort to the idea of lazy classification and mathematical apparatus of formal concept analysis to develop an abstract framework for this task. In a set of benchmarking experiments, we compare the proposed ...

Добавлено: 6 октября 2016 г.

Browsing publication data using tag clouds over concept lattices constructed by key-phrase extraction

Greene G., Dunaiski M., Fischer B. и др., , 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. P. 10–22.

Добавлено: 14 июня 2016 г.