Salvato in:
Dettagli Bibliografici
Autori principali: Chen, Yuxu, Liu, Jing, Shen, Lili, Tang, Xiaoye
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:https://arxiv.org/abs/2509.13059
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866909995039195136
author Chen, Yuxu
Liu, Jing
Shen, Lili
Tang, Xiaoye
author_facet Chen, Yuxu
Liu, Jing
Shen, Lili
Tang, Xiaoye
contents We postulate the intuitive idea of reducts of fuzzy contexts based on formal concept analysis and rough set theory. For a complete residuated lattice $L$, it is shown that reducts of $L$-contexts in formal concept analysis are interdefinable with reducts of $L$-contexts in rough set theory via negation if, and only if, $L$ satisfies the law of double negation.
format Preprint
id arxiv_https___arxiv_org_abs_2509_13059
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Reducts of fuzzy contexts: Formal concept analysis vs. rough set theory
Chen, Yuxu
Liu, Jing
Shen, Lili
Tang, Xiaoye
Logic in Computer Science
68P05, 03G10, 03B52
We postulate the intuitive idea of reducts of fuzzy contexts based on formal concept analysis and rough set theory. For a complete residuated lattice $L$, it is shown that reducts of $L$-contexts in formal concept analysis are interdefinable with reducts of $L$-contexts in rough set theory via negation if, and only if, $L$ satisfies the law of double negation.
title Reducts of fuzzy contexts: Formal concept analysis vs. rough set theory
topic Logic in Computer Science
68P05, 03G10, 03B52
url https://arxiv.org/abs/2509.13059