Using the Apriori Algorithm to Improve Rough Sets Results

Fernández-Baizán, María C.; Ruiz, Ernestina Menasalvas; Sánchez, José M. Peña; Sarrías, Juan Francisco Martínez; Millán, Socorro

doi:10.1007/3-540-45554-x_35

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…Some aspects of this problem were studied by Giles, Omlin, and Thornber (1999) in the context of fuzzy systems, by Levesque and Petrick (2002) and Levesque and Lakemeyer (2001) in the context of situation calculus, by Mangasarian, Shavlik, and Wild (2004) in the context of prior knowledge. Gálvez, Diaz, Carrión, andGarcia (2001) andFernández-Baizán andRuiz (2001) used knowledge equivalence for "CAI (Conjuntos Aproximados con Incertidumbre) model. The major contribution of the CAI model is the approximate equality among knowledge bases".…”

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confidence: 99%

Knowledge Bases Over Algebraic Models

Knyazhansky

Plotkin

2012

International Journal of Knowledge Management

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This paper discusses the informational equivalence problem for knowledge bases. The authors show that using some mathematical approach it is possible to attack this problem and end up with an implementable algorithm. An essential part of the paper is devoted to the explanation of the mathematical idea which stands behind this algorithm. The authors try to do that in common terms or, at least, in less formal terms. In the second part of the paper mathematical methods are applied to study the properties of automorphic equivalence of knowledge bases (multi-models) and show that this notion is much wider than the total isomorphism (identity) of knowledge bases. In order to make the paper self-contained, the reader is provided with the formal definition of a knowledge base. Further development of the theoretical approach presented in the paper can lead to practical applications. For example, it can be used for preventing duplication of information in knowledge bases and in other tasks of improving knowledge management.

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