Integration of Fuzzy Model Theory and FCA for Big Data Mining

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

Аннотация

In this paper, we explore two different approaches to Big Data Mining: The Fuzzy Model Theory and the Formal Concept Analysis. We carry out the integration of these two approaches for solving the problem of constructing semantic models of domains. In the present paper, we focus on the third and fourth levels of sematic models, which formalizes via case models and fuzzy models of domains. We represent the basic notions of the FCA on the fuzzy model language and describe which formula extensions formal contexts allow us to find a new knowledge about the given domain.

Язык оригиналаанглийский
Название основной публикацииSIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы961-966
Число страниц6
ISBN (электронное издание)9781728144016
DOI
СостояниеОпубликовано - окт 2019
Событие2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019 - Novosibirsk, Российская Федерация
Продолжительность: 21 окт 201927 окт 2019

Серия публикаций

НазваниеSIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings

Конференция

Конференция2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019
СтранаРоссийская Федерация
ГородNovosibirsk
Период21.10.201927.10.2019

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Palchunov, D. E., & Yakhyaeva, G. E. (2019). Integration of Fuzzy Model Theory and FCA for Big Data Mining. В SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings (стр. 961-966). [8958216] (SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIBIRCON48586.2019.8958216