Representation of “Natural” Concepts and Classes by a Hypernet Lattice of (Probabilistic) Formal Concepts

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

Abstract

In previous works, a probabilistic generalization of formal concepts was developed that is resistant to noise and is capable of restoring formal concepts. In this paper, we show that probabilistic formal concepts have a deeper meaning than the restoration of formal concepts. Probabilistic formal concepts model “natural” concepts explored in cognitive sciences and “natural” classes explored in the “natural” classification. The hyper network of probabilistic formal concepts reflects the hierarchical structure of complex patterns – a hierarchy of secondary, increasingly complex features that are found as a result of deep learning. This hierarchy, obtained by logical-probabilistic methods, in addition to being “natural”, is also explanatory, since it can give descriptions of its classes in logical-probabilistic terms. Thus, the hierarchy of probabilistic formal concepts discovered on complex images yields logical-probabilistic deep learning. The vertices of the hyper simplexes of the hyper network of probabilistic formal concepts reflect the content of “natural” concepts and classes, as they are inextricably linked with the underlying features. These vertices determine the meanings of “natural” concepts and classes, which are not reducible to the features that form them.

Original languageEnglish
Title of host publicationAdvances in Cognitive Research, Artificial Intelligence and Neuroinformatics - Proceedings of the 9th International Conference on Cognitive Sciences, Intercognsci-2020
EditorsBoris M. Velichkovsky, Pavel M. Balaban, Vadim L. Ushakov
PublisherSpringer Science and Business Media Deutschland GmbH
Pages671-676
Number of pages6
ISBN (Print)9783030716363
DOIs
Publication statusPublished - 2021
Event9th International Conference on Cognitive Sciences, Intercognsci 2020 - Moscow, Russian Federation
Duration: 10 Oct 202016 Oct 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1358 AIST
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference9th International Conference on Cognitive Sciences, Intercognsci 2020
CountryRussian Federation
CityMoscow
Period10.10.202016.10.2020

Keywords

  • Clustering
  • Concept
  • Hypernet lattice
  • Probabilistic formal concept

OECD FOS+WOS

  • 1.02 COMPUTER AND INFORMATION SCIENCES

Fingerprint

Dive into the research topics of 'Representation of “Natural” Concepts and Classes by a Hypernet Lattice of (Probabilistic) Formal Concepts'. Together they form a unique fingerprint.

Cite this