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FCA-Based Models and a Prototype Data Analysis System for Crowdsourcing Platforms
P. 173–192.
This paper considers a data analysis system for collaborative platforms which was developed by the joint research team of the National Research University Higher School of Economics and the Witology company. Our focus is on describing the methodology and results of the first experiments. The developed system is based on several modern models and methods for analysing of object-attribute and unstructured data (texts) such as Formal Concept Analysis, multimodal clustering, association rule mining, and keyword and collocation extraction from texts.
In book
Vol. 7735: Conceptual Structures for STEM Research and Education, 20th International Conference on Conceptual Structures. , Berlin, Heidelberg: Springer, 2013.
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
Cham: Springer, 2024.
This multi-volume set, LNAI 14941 to LNAI 14950, constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2024, held in Vilnius, Lithuania, in September 2024. ...
Added: November 22, 2024
Shanghai: IEEE Computer Society, 2023.
The IEEE International Conference on Data Mining (ICDM) has established itself as the world’s premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, ...
Added: March 20, 2024
D'yakonov A., Головина А. М., Прикладная математика и информатика 2023 Т. 61 № 74 С. 91–108
A methodology for finding patterns by solving machine learning problems with a teacher is described and applied to the analysis of national victimization survey data. Important features for machine learning models, interesting patterns and inconsistencies in the data are found. Experiments on estimating feature importance using different methods are described. ...
Added: March 18, 2024
Анташева М. С., Lobanova P., Isaeva J. K. et al., Социология: методология, методы, математическое моделирование 2023 № 57 С. 7–41
The information agenda broadcast by Chinese media resources is a source of up-to-date data on public opinion on key issues of social welfare. Due to the technical peculiarities of the organization of Chinese websites and the need to attract additional resources for automatic processing (parsing) of texts in Chinese, this topic is not widely represented in domestic and foreign studies. The ...
Added: November 9, 2023
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
Springer, 2023.
This book presents the state-of-the-art in the emerging field of data science and includes models for layered security with applications in the protection of sites—such as large gathering places—through high-stake decision-making tasks. Such tasks include cancer diagnostics, self-driving cars, and others where wrong decisions can possibly have catastrophic consequences. Additionally, this book provides readers with ...
Added: August 31, 2023
Springer, 2023.
This book constitutes the extended and revised versions of a set of selected papers from the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2021, on October 25–27, 2021. The conference was held virtually due to the COVID-19 crisis.
The 9 full papers included in this book were carefully reviewed and ...
Added: July 8, 2023
Ignatov D. I., Lobachevskii Journal of Mathematics 2023 No. 44 P. 137–146
We consider two ways how to compute the number of maximal antichains in the Boolean lattice on 𝑛 elements. The first one is based on full direct enumeration, while the second ones relies on concept lattices or Galois lattices (studied in Formal Concept Analysis, an applied branch of lattice theory) and the Dedekind–MacNeille completion of a partial ...
Added: June 13, 2023
Золотухина М. А., Zykov S. V., Вестник Российского нового университета 2023 № 1 С. 20–28
Зачастую именно человеческий фактор ведет к распространению угроз на предприятиях. Если техническое устройство представляет собой четко работающий и слаженный механизм с возможностью при помощи диагностического оборудования проводить замеры параметров неисправностей и устранять их, то для исследования скрытых атак необходим новый компонент системы. Предприятия и промышленность в целом нуждаются в интеллектуальной системе защиты и обнаружения скрытых ...
Added: April 11, 2023
Springer, 2023.
This book constitutes the proceedings of Third International Conference on Information Systems and Design, ICID 2022, which took place in Tashkent, Uzbekistan, in September 2022.
The 12 papers presented in this volume were carefully reviewed and selected from 35 submissions. They were organized in topical sections as follows: methodological support of analysis and management tools: theoretical-focused ...
Added: March 31, 2023
Lukianchenko P., Gromov V., Beschastnov Y. et al., Вестник кибернетики 2022 Т. 4 № 48 С. 37–48
The study analyzes the time series of the number of new cases in the administrative courts
of the Russian Federation using two methods of time series grouping according to the chaotic, stochastic, and
regular structure. The first model is based on the entropy‒complexity plane, the second one is presented by the
attribute‒object graph. As a result, four groups ...
Added: March 20, 2023
Gromov V., Урманцева Н. Р., [б.и.], 2021.
В докладе рассматриваются подходы к прогнозированию на основе кластеризации, опирающиеся на методологию анализа формальных понятий. Методология применяется для кластеризации участков временного ряда с целью выделения характерных участков (мотивов), отвечающих больным с различной степенью засорённости фистулы. ...
Added: January 30, 2023
Ilya Semenkov, Sergei O. Kuznetsov, , in: Proceedings of the 9th International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2021)Vol. 2972.: CEUR-WS, 2021. P. 105–112.
This paper presents different versions of classification ensemble methods based on pattern structures. Each of these methods is described and tested on multiple datasets (including datasets with exclusively numerical and exclusively nominal features). As a baseline model Random Forest generation is used. For some classification tasks the classification algorithms based on pattern structures showed better ...
Added: December 19, 2022
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
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
Muratova A., Ignatov D. I., Mitrofanova E., , 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. 297–299.
This is the extended abstract of a case study on demographic sequences analysis by machine learning and data mining methods. ...
Added: November 1, 2022