A data mining approach to computational taxonomy

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 domai...

Descripción completa

Detalles Bibliográficos
Autores principales:	Perichinsky, Gregorio, García Martínez, Ramón
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2000
Materias:	Ciencias Informáticas Computational Taxonomy Taxonomy Insufficient database Knowledge discovery Data mining base de datos Clustering
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/22154
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-22154
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas Computational Taxonomy Taxonomy Insufficient database Knowledge discovery Data mining base de datos Clustering
spellingShingle	Ciencias Informáticas Computational Taxonomy Taxonomy Insufficient database Knowledge discovery Data mining base de datos Clustering Perichinsky, Gregorio García Martínez, Ramón A data mining approach to computational taxonomy
topic_facet	Ciencias Informáticas Computational Taxonomy Taxonomy Insufficient database Knowledge discovery Data mining base de datos Clustering
description	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.
format	Objeto de conferencia Objeto de conferencia
author	Perichinsky, Gregorio García Martínez, Ramón
author_facet	Perichinsky, Gregorio García Martínez, Ramón
author_sort	Perichinsky, Gregorio
title	A data mining approach to computational taxonomy
title_short	A data mining approach to computational taxonomy
title_full	A data mining approach to computational taxonomy
title_fullStr	A data mining approach to computational taxonomy
title_full_unstemmed	A data mining approach to computational taxonomy
title_sort	data mining approach to computational taxonomy
publishDate	2000
url	http://sedici.unlp.edu.ar/handle/10915/22154
work_keys_str_mv	AT perichinskygregorio adataminingapproachtocomputationaltaxonomy AT garciamartinezramon adataminingapproachtocomputationaltaxonomy AT perichinskygregorio dataminingapproachtocomputationaltaxonomy AT garciamartinezramon dataminingapproachtocomputationaltaxonomy
bdutipo_str	Repositorios
_version_	1764820465604362243

A data mining approach to computational taxonomy

Ejemplares similares