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Listar por autor "Marcén Terraza, Ana Cristina"

Mostrando ítems 1-5 de 5

Design of a Machine Learning-based Approach for Fragment Retrieval on Models

Marcén Terraza, Ana Cristina (Universitat Politècnica de València, 2021-01-10)

[ES] El aprendizaje automático (ML por sus siglas en inglés) es conocido como la rama de la inteligencia artificial que reúne algoritmos estadísticos, probabilísticos y de optimización, que aprenden empíricamente. ML puede ...
Evaluating the benefits of empowering model-driven development with a machine learning classifier

Marcén, Ana C.; Pérez, Francisca; Pastor López, Oscar; Cetina, Carlos (John Wiley & Sons, 2022-11)

[EN] Increasingly, the model driven engineering (MDE) community is paying more attention to the techniques offered by the machine learning (ML) community. This has led to the application of ML techniques to MDE related ...
Hacia la Caracterización de las Aplicaciones Big Data

Marcen Terraza, Ana Cristina; Cetina Englada, Carlos; Pastor López, Oscar (Universitat Politècnica de València, 2019-02-06)

Mediante este artículo proponemos el uso de una ontología como base esencial para construir aplicaciones Big Data determinando qué se entiende por aplicación Big Data, cuáles son sus características particulares o de qué ...
On the influence of model fragment properties on a machine learning-based approach for feature location

Ballarin, Manuel; Marcén, Ana C.; Pelechano Ferragud, Vicente; Cetina, Carlos (Elsevier, 2021-01)

[EN] Context: Leveraging machine learning techniques to address feature location on models has been gaining attention. Machine learning techniques empower software product companies to take advantage of the knowledge and ...
Traceability Link Recovery between Requirements and Models using an Evolutionary Algorithm Guided by a Learning to Rank Algorithm: Train control and management case

Marcén, Ana C.; Lapeña, Raúl; Pastor López, Oscar; Cetina, Carlos (Elsevier, 2020-05)

[EN] Traceability Link Recovery (TLR) has been a topic of interest for many years within the software engineering community. In recent years, TLR has been attracting more attention, becoming the subject of both fundamental ...