Model-Driven Technologies for Data Mining Democratisation

Vega Ruiz, Alfonso de la; Sánchez Barreiro, Pablo

dc.contributor.author	Vega Ruiz, Alfonso de la
dc.contributor.author	Sánchez Barreiro, Pablo
dc.contributor.other	Universidad de Cantabria	es_ES
dc.date.accessioned	2020-10-13T18:25:00Z
dc.date.available	2020-10-13T18:25:00Z
dc.date.issued	2019
dc.identifier.issn	1613-0073
dc.identifier.other	TIN2017-86520-C3-3-R
dc.identifier.uri	http://hdl.handle.net/10902/19330
dc.description.abstract	Data mining techniques allow discovering insights previously hidden in data from a domain. However, these techniques demand very specialised skills. People often lack these skills, which hinders data mining democratisation. To alleviate this situation, we defined a model-driven framework and some domain-specific languages that contribute to the democratisation of data mining. Here we summarise these contributions.	es_ES
dc.format.extent	6 p.	es_ES
dc.language.iso	eng	es_ES
dc.publisher	R. Piskac c/o Redaktion Sun SITE Informatik V RWTH Aachen	es_ES
dc.rights	Attribution 4.0 International	es_ES
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.source	CEUR-WS.org/Vol-2405/03_paper	es_ES
dc.subject.other	Model-Driven Engineering	es_ES
dc.subject.other	Domain-Specific Languages	es_ES
dc.subject.other	Data Mining	es_ES
dc.subject.other	Data Mining Democratisation	es_ES
dc.title	Model-Driven Technologies for Data Mining Democratisation	es_ES
dc.type	info:eu-repo/semantics/conferenceObject	es_ES
dc.relation.publisherVersion	http://ceur-ws.org/Vol-2405/03_paper.pdf	es_ES
dc.rights.accessRights	openAccess	es_ES
dc.type.version	publishedVersion	es_ES