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Título: A data mining approach to computational taxonomy
Autores: Perichinsky, Gregorio
García Martínez, Ramón
Fecha: 2012-10-10
2000-05
2000
Publicador: Unversidad Nacional de La Plata
Fuente:

Tipo: Objeto de conferencia
Objeto de conferencia
Tema: Computational Taxonomy
Taxonomy
Insufficient database
Knowledge discovery
Data mining
Clustering
Ciencias Informáticas
base de datos
Descripción: This study investigates an approach of knowledge discovery and data mining in insufficient databases. An application of Computational Taxonomy analysis demonstrates that the approach is effective in such a data mining process. The approach is characterized by the use ot both the second type of domain knowledge and visualization. This type of knowledge is newly defined in this study and deduced from supposition about background situations of the domain. The supposition is triggered by strong intuition about the extracted features in a recurrent process of data mining. This type of domain knowledge is useful not only for discovering interesting knowledge but al so tor guiding the subsequent search for more explicit and interesting knowledge. The visualization is very useful for triggering the supposition.
Eje: Ingeniería de software y base de datos
Idioma: Inglés