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dc.contributor.authorCueva-Lovelle, Juan Manuel
dc.contributor.authorGarcía-Díaz, Vicente
dc.contributor.authorPelayo G-Bustelo, Cristina
dc.contributor.authorPascual-Espada, Jórdan
dc.date2015
dc.date.accessioned2020-06-12T09:23:03Z
dc.date.available2020-06-12T09:23:03Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/10169
dc.description.abstractMachine learning is one of the most important subfields of computer science and can be used to solve a variety of interesting artificial intelligence problems. There are different languages, framework and tools to define the data needed to solve machine learning-based problems. However, there is a great number of very diverse alternatives which makes it difficult the intercommunication, portability and re-usability of the definitions, designs or algorithms that any developer may create. In this paper, we take the first step towards a language and a development environment independent of the underlying technologies, allowing developers to design solutions to solve machine learning-based problems in a simple and fast way, automatically generating code for other technologies. That can be considered a transparent bridge among current technologies. We rely on Model-Driven Engineering approach, focusing on the creation of models to abstract the definition of artifacts from the underlying technologies.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 3, nº 5
dc.relation.urihttps://www.ijimai.org/journal/bibcite/reference/2508es_ES
dc.rightsopenAccesses_ES
dc.subjectMDEes_ES
dc.subjectDSLes_ES
dc.subjectartificial intelligencees_ES
dc.subjectmachine learninges_ES
dc.subjectXtextes_ES
dc.subjectIJIMAIes_ES
dc.titleTowards a Standard-based Domain-specific Platform to Solve Machine Learning-based Problemses_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttps://doi.org/10.9781/ijimai.2015.351


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