Integration of Fuzzy Model Theory and FCA for Big Data Mining

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationSIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages961-966
Number of pages6
ISBN (Electronic)9781728144016
DOIs
Publication statusPublished - Oct 2019
Event2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019 - Novosibirsk, Russian Federation
Duration: 21 Oct 201927 Oct 2019

Publication series

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

Conference

Conference2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019
CountryRussian Federation
CityNovosibirsk
Period21.10.201927.10.2019

Keywords

  • associative rule
  • Boolean-valued model
  • case model
  • formal concept
  • formal context
  • formula extension of formal context
  • fuzzy model
  • fuzzy model theory
  • semantic model

Fingerprint Dive into the research topics of 'Integration of Fuzzy Model Theory and FCA for Big Data Mining'. Together they form a unique fingerprint.

  • Cite this

    Palchunov, D. E., & Yakhyaeva, G. E. (2019). Integration of Fuzzy Model Theory and FCA for Big Data Mining. In SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings (pp. 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