Alpha galois lattices. Ventos, V., Soldano, H., & Lamadon, T. In Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004, pages 555-558, 2004. abstract bibtex In many applications there is a need to represent a large number of data by clustering them in a hierarchy of classes. Our basic representation is a Galois lattice, a structure that exhaustively represents the whole set of concepts that are distinguishable given the instance set and the representation language. What we propose here is a method to reduce the size of the lattice, and thus simplify our view of the data, while conserving its formal structure and exhaustivity. For that purpose we use a preliminary partition of the instance set, representing the association of a "type" to each instance. By redefining the notion of extent of a term in order to cope, to a certain degree (denoted as α), with this partition, we define a particular family of Galois lattices denoted as alpha Galois lattices. We also discuss the related implication rules defined as inclusion of such α-extents.
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abstract = {In many applications there is a need to represent a large number of data by clustering them in a hierarchy of classes. Our basic representation is a Galois lattice, a structure that exhaustively represents the whole set of concepts that are distinguishable given the instance set and the representation language. What we propose here is a method to reduce the size of the lattice, and thus simplify our view of the data, while conserving its formal structure and exhaustivity. For that purpose we use a preliminary partition of the instance set, representing the association of a "type" to each instance. By redefining the notion of extent of a term in order to cope, to a certain degree (denoted as α), with this partition, we define a particular family of Galois lattices denoted as alpha Galois lattices. We also discuss the related implication rules defined as inclusion of such α-extents.},
bibtype = {inProceedings},
author = {Ventos, Véronique and Soldano, Henry and Lamadon, Thibaut},
booktitle = {Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004}
}
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