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Анализ тримодальных данных на примере Интернет-сервисов социальных закладок
С. 315–322.
Ignatov D. I., Magizov R. A.
![Социологические методы в современной исследовательской практике: Сборник статей, посвященный памяти первого декана факультета социологии НИУ ВШЭ А.О. Крыштановского [Электронный ресурс]](/pubs/share/cover/thumb/67397924:r320x580.jpg)
Budnik R., Журнал зарубежного законодательства и сравнительного правоведения 2026 Т. 22 № 2 С. 15–26
This article examines the precedential cooperation between the governmental and business entities in eradicating piracy in the informational area of China. The purpose of the study is to analyze the unique empirical approach to the implementation of public policy aimed at restoring the effective functioning of mechanisms for the protection and enforcement of intellectual property ...
Added: April 27, 2026
Diskin E., Труды по интеллектуальной собственности 2023 Т. 45 № 2 С. 17–24
The article considers a new issue for the court practice of protection of the right to the account (account) of the Internet platform. A study of Russian jurisprudence on this issue suggests that this right should not be considered solely in the context of civil law relations but is also a protected constitutional right guaranteed ...
Added: June 19, 2023
Ignatov D. I., Иванова П., Замалетдинова А., , in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & StatisticsVol. 315.: Springer, 2020. Ch. 2 P. 19–35.
This paper is related to the problem of finding the maximal quasi-bicliques in a bipartite graph (bigraph). A quasi-biclique in the bigraph is its “almost” complete subgraph. The relaxation of completeness can be understood variously; here, we assume that the subgraph is a \(\gamma \)-quasi-biclique if it lacks a certain number of edges to form ...
Added: February 22, 2020
Ignatov D. I., Yurov M., , in: Rough Sets - International Joint Conference, IJCRS 2017, Olsztyn, Poland, July 3-7, 2017, Proceedings, Part II.Vol. 10314.: Springer, 2017. P. 558–569.
Mining ternary relations or triadic Boolean tensors is one of the recent trends in knowledge discovery that allows one to take into account various modalities of input object-attribute data. For example, in movie databases like IMBD, an analyst may find not only movies grouped by specific genres but see their common keywords. In the so-called ...
Added: February 9, 2020
Ignatov D. I., Ivanova P., Zamaletdinova A. et al., , in: Supplementary Proceedings ICFCA 2019 Conference and WorkshopsVol. 2378.: CEUR Workshop Proceedings, 2019. P. 28–32.
This short paper is related to the problem of finding maximum quasi-bicliques in a bipartite graph (bigraph). A quasi-biclique in a bigraph is its “almost” complete subgraph; here, we assume that the subgraph is a quasi-biclique if it lacks γ · 100% of the edges to become a biclique. The problem of finding the maximal ...
Added: October 31, 2019
Ignatov D. I., Semenov A., Комиссарова Д. В. et al., , in: Formal Concept Analysis of Social Networks.: Springer, 2017. Ch. 4 P. 59–96.
Multimodal clustering is an unsupervised technique for mining interesting patterns in n-ary relations or n-mode networks. Among different types of such generalised patterns one can find biclusters and formal concepts (maximal bicliques) for two-mode case, triclusters and triconcepts for three-mode case, closed n-sets for n-mode case, etc. Object-attribute biclustering (OA-biclustering) for mining large binary datatables (formal contexts or two-mode ...
Added: December 17, 2017
Зудин С., Gnatyshak D. V., Ignatov D. I., , in: Proceedings of the Twelfth International Conference on Concept Lattices and Their Applications Clermont-Ferrand, France, October 13-16, 2015Vol. 1466.: Clermont-Ferrand: CEUR Workshop Proceedings, 2015. P. 47–58.
In our previous work an efficient one-pass online algorithm
for triclustering of binary data (triadic formal contexts) was proposed.
This algorithm is a modified version of the basic algorithm for OAC-triclustering
approach; it has linear time and memory complexities. In
this paper we parallelise it via map-reduce framework in order to make
it suitable for big datasets. The results of ...
Added: October 23, 2015
Ignatov D. I., Gnatyshak D. V., Sergei O. Kuznetsov et al., Machine Learning 2015 Vol. 101 No. 1 P. 271–302
This paper presents several definitions of “optimal patterns” in triadic data and results of experimental comparison of five triclustering algorithms on real-world and synthetic datasets. The evaluation is carried over such criteria as resource efficiency, noise tolerance and quality scores involving cardinality, density, coverage, and diversity of the patterns. An ideal triadic pattern is a totally dense ...
Added: April 15, 2015
Гнатышак Д. В., Научно-техническая информация. Серия 2: Информационные процессы и системы 2015 № 2 С. 16–30
В связи с продолжающимся ростом популярности области больших данных все более активно ставится вопрос о создании эффективных алгоритмов с низкой временной сложностью и возможностью параллелизации. Целью данной работы было создание эффективного однопроходного алгоритма трикластеризации бинарных данных, пригодного для использования в области больших данных. В результате был получен однопроходный линейный онлайн-алгоритм OAC-трикластеризации (трикластеризации объект-признак-условие). Помимо того, ...
Added: April 15, 2015
Kashnitsky Y., В кн.: Труды Международной конференции по физико-технической информатике CPT-2013, 12-19 мая 2013 г., Ларнака, Республика Кипр.: М., Протвино: Изд-во ИФТИ, 2013. С. 251–258.
Triclustering is an outgrowth of Formal Concept Analysis intented to detect groups of objects with similar properties (clusters) in a context of three sets of entities. In case of social network analysis,
for instance, these sets might be users, their interests and events they take part in. Triclustering here can help to detect users with similar ...
Added: January 27, 2014
Los Alamitos: IEEE Computer Society, 2013.
Proceedings of IEEE 10th International Conference on e-Business Engineering (ICEBE), 2013 ...
Added: January 21, 2014
Komarov M. M., Maltseva S. V., , in: Human Rights on the Internet: Legal Frames and Technological ImplicationsIssue 2.: M.: Higher School of Economics Publishing House, 2013. Ch. 1 P. 60–68.
Due to the technological development we faced problem of not implementing new technologies in order to help displaced people and refugees or sometimes we only introduce some basic services. It is necessary to remind about disasters which we unfortunately can’t predict and which usually completely change citizens’ life. People have to move from their neighborhood ...
Added: December 20, 2013
Kashnitsky Y., Труды Московского физико-технического института 2014 Т. 6 № 3 С. 43–56
Triclustering is an outgrowth of Formal Concept Analysis intented to detect groups of objects with similar properties (clusters) in a context of three sets of entities. In case of social network analysis, for instance, these sets might be users, their interests and events they take part in. Triclustering here can help to detect users with ...
Added: November 8, 2013
Ignatov D. I., Kuznetsov S., Zhukov L. E. et al., International Journal of General Systems 2013 Vol. 42 No. 6 P. 572–593
formal concept analysis,
data mining,
triclustering,
three-way data,
folksonomy,
spectral triclustering ...
Added: October 16, 2013
Секинаева З. Р., Ignatov D. I., В кн.: Анализ изображений, сетей и текстов. Доклады всероссийской научной конференции АИСТ'12. Модели, алгоритмы и инструменты анализа данных; результаты и возможности для анализа изображений, сетей и текстов. Екатеринбург, 16 – 18 марта 2012 годаВып. 1.: М.: Национальный открытый университет «ИНТУИТ», 2012. С. 246–254.
Статья посвящена разработке метода трикластеризации на основе графовой спектральной кластеризации. В серии экспериментов на реальных данных исследована эффективность и пригодность метода к анализу данных систем совместного пользования ресурсами, т.н. фолксономий ...
Added: January 30, 2013
Ignatov D. I., Kuznetsov S., Poelmans J., В кн.: Математические методы распознавания образов: 15-я Всероссийская конференция, г.Петрозаводск, 11–17 сентября 2011 г.: Сборник докладов.: М.: МАКС Пресс, 2012. С. 258–261.
В работе предложен новый подход к трикластеризации трехмерных бинарных данных. Трикластер определен в терминах триадического анализа формальных понятий (Triadic Formal Concept Analysis) как плотное тримножество тернарного отношения Y между объектами, признаками и условиями. Такое определение является ослаблением определения трипонятия и дает возможность найти все трикластеры и трипонятия, содержащиеся в трикластерах больших наборов данных. Данный подход ...
Added: December 4, 2012
Ignatov D. I., Kuznetsov S., Zhukov L. E., , in: Rough Sets, Fuzzy Sets, Data Mining and Granular Computing: 13th International Conference, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011. ProceedingsVol. 6743.: Berlin, Heidelberg: Springer, 2011. P. 257–264.
A novel approach to triclustering of a three-way binary data is proposed. Tricluster is defined in terms of Triadic Formal Concept Analysis as a dense triset of a binary relation Y , describing relationship between objects, attributes and conditions. This definition is a relaxation of a triconcept notion and makes it possible to find all ...
Added: December 3, 2012
Gnatyshak D. V., Ignatov D. I., Semenov A. et al., , in: Perspectives in Business Informatics Research. 11th International Conference, BIR 2012, Nizhny Novgorod, Russia, September 2012 ProceedingsIssue 128.: Berlin, Heidelberg: Springer, 2012. P. 162–171.
We combine bi- and triclustering to analyse data collected from the Russian online social network Vkontakte. Using biclustering we extract groups of users with similar interests and find communities of users which belong to similar groups. With triclustering we reveal users' interests as tags and use them to describe Vkontakte groups. After this social tagging ...
Added: December 3, 2012
Gnatyshak D. V., Ignatov D. I., Semenov A. et al., , in: Concept Discovery in Unstructured Data. 2nd International Workshop, CDUD 2012, Leuven, Belgium, May 2012, ProceedingsIssue 871.: Leuven: Katholieke Universiteit Leuven, 2012. P. 30–39.
In this paper we propose two novel methods for analyzing data collected from online social networks. In particular we will do analyses on Vkontake data (Russian online social network). Using biclustering we extract groups of users with similar interests and find communities of users which belong to similar groups. With triclustering we reveal users’ interests ...
Added: November 20, 2012