@article{2508,
  keywords = {MDE, DSL, Artificial Intelligence, Machine Learning, Xtext},
  author = {Juan Manuel Cueva-Lovelle and Vicente García-Díaz and Cristina Pelayo G-Bustelo and Jordán Pascual-Espada},
  title = {Towards a Standard-based Domain-specific Platform to Solve Machine Learning-based Problems},
  abstract = {Machine 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.},
  year = {2015},
  journal = {International Journal of Interactive Multimedia and Artificial Intelligence},
  volume = {3},
  number = {5},
  pages = {6-12},
  month = {12/2015},
  issn = {1989-1660},
  url = {http://www.ijimai.org/journal/sites/default/files/files/2015/11/ijimai20153_5_1_pdf_15294.pdf},
  doi = {10.9781/ijimai.2015.351},
}