Autor: |
Manuel Ojeda-Hernández, Francisco Pérez-Gámez, Domingo López-Rodríguez, Nicolás Madrid, Ángel Mora |
Jazyk: |
angličtina |
Rok vydání: |
2022 |
Předmět: |
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Zdroj: |
International Journal of Computational Intelligence Systems, Vol 15, Iss 1, Pp 1-16 (2022) |
Druh dokumentu: |
article |
ISSN: |
1875-6883 |
DOI: |
10.1007/s44196-022-00123-3 |
Popis: |
Abstract Formal concept analysis is a data analysis framework based on lattice theory. In this paper, we analyse the use, inside this framework, of positive and negative (mixed) attributes of a dataset, which has proved to represent more information on the use of just positive attributes. From a theoretical point of view, in this paper we show the structure and the relationships between minimal generators of the simple and mixed concept lattices. From a practical point of view, the obtained theoretical results allow us to ensure a greater granularity in the retrieved information. Furthermore, due to the relationship between FCA and Knowledge Space theory, on a practical level, we analyse the marks of a Mathematics course to establish the knowledge structure of the course and determine the key items providing new relevant information that is not evident without the use of the proposed tools. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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