Concept similarity in formal concept analysis
Abstract
The identification of syntactically different concepts that are semantically similar, also referred to as Similarity Reasoning, is fundamental in several research areas such as Artificial Intelligence, Software Engineering, Cognitive Science and, in particular, in Semantic Web. Formal Concept Analysis (FCA) is a mathematical framework which is revealing very interesting in supporting fundamental activities for the development of Semantic Web. In order to model uncertainty information, FCA with many-valued contexts is addressed and, in particular, FCA with Ordinal scaling (OFCA), and FCA with Interordinal scaling (IFCA). Concept similarity in IFCA, i.e., in many-valued contexts where attribute values are intervals, is a problem that has been marginally investigated, although the increasing interest in the literature in this topic.
Copyright © 2022 Anna Formica. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article
A. Formica, Concept similarity in formal concept analysis, J. Math. Comput. Sci. 12 (2022), 171. https://doi.org/10.28919/jmcs/7406
BibTeX
@article{Formica2022,
author = {Formica, Anna},
title = {Concept similarity in formal concept analysis},
journal = {J. Math. Comput. Sci.},
volume = {12},
year = {2022},
pages = {171},
doi = {10.28919/jmcs/7406}
}