Bimorphisms and attribute implications in heterogeneous formal contexts

IF 3.2 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ľubomír Antoni , Peter Eliaš , Ján Guniš , Dominika Kotlárová , Stanislav Krajči , Ondrej Krídlo , Pavol Sokol , Ľubomír Šnajder
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引用次数: 0

Abstract

Formal concept analysis is a powerful mathematical framework based on mathematical logic and lattice theory for analyzing object-attribute relational systems. Over the decades, Formal concept analysis has evolved from its theoretical foundations into a versatile methodology applied across various disciplines. A heterogeneous formal context provides a feasible generalization of a formal context, enabling diverse truth-degrees of objects, attributes, and fuzzy relations. In our paper, we present extended theoretical results on heterogeneous formal contexts, including bimorphisms, Galois connections, and heterogeneous attribute implications. We recall the basic notions and properties of the heterogeneous formal context and its concept lattice. Moreover, we present extended results on bimorphisms and Galois connections in a heterogeneous formal context, including a self-contained proof of the main result. We include examples of introduced notions in heterogeneous formal contexts and two-valued logic. We propose the extension of attribute implications for heterogeneous formal contexts and explore their validity. By embracing heterogeneity in Formal concept analysis, we enrich its extended theoretical foundations and pave the way for innovative applications across diverse domains, including personal data protection and cybersecurity.

异质形式语境中的双态性和属性含义
形式概念分析是一种基于数理逻辑和网格理论的强大数学框架,用于分析对象属性关系系统。几十年来,形式概念分析已从其理论基础发展成为一种应用于各学科的通用方法。异构形式语境为形式语境提供了可行的概括,使对象、属性和模糊关系的真度多样化成为可能。在本文中,我们介绍了关于异质形式语境的扩展理论成果,包括双形态、伽罗伊连接和异质属性蕴涵。我们回顾了异质形式语境及其概念网格的基本概念和属性。此外,我们还介绍了关于异质形式语境中的双态性和伽罗瓦连接的扩展结果,包括主要结果的自足证明。我们还举例说明了在异构形式语境和二值逻辑中引入的概念。我们提出了属性含义在异质形式语境中的扩展,并探讨了其有效性。通过拥抱形式概念分析中的异质性,我们丰富了其扩展的理论基础,并为个人数据保护和网络安全等不同领域的创新应用铺平了道路。
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来源期刊
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning 工程技术-计算机:人工智能
CiteScore
6.90
自引率
12.80%
发文量
170
审稿时长
67 days
期刊介绍: The International Journal of Approximate Reasoning is intended to serve as a forum for the treatment of imprecision and uncertainty in Artificial and Computational Intelligence, covering both the foundations of uncertainty theories, and the design of intelligent systems for scientific and engineering applications. It publishes high-quality research papers describing theoretical developments or innovative applications, as well as review articles on topics of general interest. Relevant topics include, but are not limited to, probabilistic reasoning and Bayesian networks, imprecise probabilities, random sets, belief functions (Dempster-Shafer theory), possibility theory, fuzzy sets, rough sets, decision theory, non-additive measures and integrals, qualitative reasoning about uncertainty, comparative probability orderings, game-theoretic probability, default reasoning, nonstandard logics, argumentation systems, inconsistency tolerant reasoning, elicitation techniques, philosophical foundations and psychological models of uncertain reasoning. Domains of application for uncertain reasoning systems include risk analysis and assessment, information retrieval and database design, information fusion, machine learning, data and web mining, computer vision, image and signal processing, intelligent data analysis, statistics, multi-agent systems, etc.
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