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Organizing Contexts as a Lattice of Decision Trees for Machine Reading Comprehension
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, we build an environment of supported decision trees for the MRC task. Each answer is represented by a path of a supported decision tree and the whole corpus of answers is then form a lattice of supported decision trees. This environment gives a boost to MRC performance, handling cases where it is nontrivial to determine which document/passage MRC needs to be applied to.
In book
Vol. 3233. , CEUR Workshop Proceedings, 2022.
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
Ignatov D. I., , 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. 47–56.
The paper aims at not only counting how many basic choice functions exist on a finite set of alternatives (all, non-empty, single-element valued) but shows how to do this with the help of Formal Concept Analysis. Moreover, we introduce the contextual representation of a choice function by considering the formal context of its map from ...
Added: November 23, 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
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
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
Shadrina E. V., Вестник Нижегородского университета им. Н.И. Лобачевского. Серия: Социальные науки 2022 № 3(67) С. 229–236
The article discusses the influence of temperament on the academic performance of the first-year students at HSENizhny Novgorod on the example of the Faculty of Informatics, Mathematics and Computer Science. Analysis was held with the help of statistics methods and methods of data mining. The baseline data for the study is information about students, collected ...
Added: October 18, 2022
Chistopolskaia A., Podolskii V. V., Theory of Computing Systems 2022
In this paper we study decision tree models with various types of queries. For a given function it is usually not hard to determine the complexity in the standard decision tree model (each query evaluates a variable). However in more general settings showing tight lower bounds is substantially harder. Threshold functions often have non-trivial complexity ...
Added: September 13, 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
Galitsky B., Ilvovsky D., Goncharova E., , in: Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2021.: INCOMA Ltd, 2021. P. 444–453.
Added: October 28, 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
Kravchenko T. K., Shevgunov T., , in: Informatics and Cybernetics in Intelligent Systems: Proceedings of 10th Computer Science On-line Conference 2021Vol. 3.: Cham: Springer, 2021. P. 230–240.
properly built risk assessment process could help to significantly
reduce the overall level of a project uncertainty, which in turn will have a positive
impact on the project outcome. Based on recommendation given in BABOK®
Guide, a combined procedure for analysis of risks is built up, which allows performing
risk assessment within the framework of the overall risk management
process. ...
Added: September 26, 2021
Vyalyi M., Problems of Information Transmission 2021 Vol. 57 No. 2 P. 143–160
We consider a generalization of the Pólya–Kasteleyn approach to counting the number of perfect matchings in a graph based on computing the symbolic Pfaffian of a directed adjacency matrix of the graph. Complexity of algorithms based on this approach is related to the complexity of the sign function of a perfect matching in generalized decision ...
Added: August 20, 2021
Aleksandrova M., ИНТЕРакция. ИНТЕРвью. ИНТЕРпретация 2021 Т. 13 № 2 С. 81–96
Text mining has developed rapidly in recent years. In this article, we compare classification methods that are suitable for solving problems of predicting item nonresponse. The author builds reasoning about how the analysis of textual data can be implemented in a wider research field based on this material. The author considers a number of metrics ...
Added: August 20, 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
Educational Data Mining for Prediction of Academically Risky Students Depending on their Temperament
Korenkova M., Shadrina E. V., Oshmarina O. 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. 277–290.
The article discusses the influence of temperament on the academic performance of the first-year students at HSE-Nizhny Novgorod on the example of the Faculty of Informatics, Mathematics and Computer Science (IM&CS). The analyses were done with the help of statistics and educational data mining. The baseline data for the study is information about students, obtained ...
Added: December 6, 2020
Lukianova A., Nikulin E., Zinchenko A., Investment Management and Financial Innovations 2017 Vol. 14 No. 2 P. 264–280
The purpose of the current paper is to elaborate a model to forecast a particular type of
earnings management by companies: upward earnings management, downward earnings
management or the absence of significant manipulation.
The sample analyzed in the current paper comprises 664 Russian and 2,380 Chinese
public companies for the period 2009–2014. The forecast was made for 2014 based ...
Added: November 25, 2020
Bogdanova T., Камалова А. Р., Kravchenko T. K. et al., Бизнес-информатика 2020 Т. 14 № 3 С. 7–23
The solution of the housing problem for many decades has been and remains one of the most important tasks facing the nation.. The problem of modeling the value of residential properties is becoming more and more urgent, since a high-quality forecast makes it possible to reduce risks, both for government bodies and for realtors specializing ...
Added: October 8, 2020