Antonio Jesús Fernández-García

发表

TvCSL: An XML-Based Language for the Specification of TV-Component Applications

Javier Criado, Luis Iribarne, Jesús Vallecillos, 2011, WSKS.

Creating a Recommender System to Support Higher Education Students in the Subject Enrollment Decision

Juan Carlos Preciado, Antonio Jesús Fernández-García, Roberto Rodríguez-Echeverría, 2020, IEEE Access.

A Web Services Infrastructure for the Management of Mashup Interfaces

Javier Criado, Luis Iribarne, Nicolás Padilla, 2015, ICSOC Workshops.

A flexible data acquisition system for storing the interactions on mashup user interfaces

James Zijun Wang, Javier Criado, Luis Iribarne, 2018, Comput. Stand. Interfaces.

An Implementation of a Trading Service for Building Open and Interoperable DT Component Applications

Luis Iribarne, Antonio Jesús Fernández-García, Carmelo Maturana, 2011, PAAMS.

A microservice-based architecture for enhancing the user experience in cross-device distributed mashup UIs with multiple forms of interaction

James Z. Wang, Luis Iribarne, Antonio Jesús Fernández-García, 2017, Universal Access in the Information Society.

A Comparison of Feature Selection Methods to Optimize Predictive Models Based on Decision Forest Algorithms for Academic Data Analysis

Antonio Corral, Javier Criado, Luis Iribarne, 2018, WorldCIST.

Evolving Mashup Interfaces Using a Distributed Machine Learning and Model Transformation Methodology

James Zijun Wang, Luis Iribarne, Antonio Jesús Fernández-García, 2015, OTM Workshops.

A recommender system for component-based applications using machine learning techniques

James Zijun Wang, Javier Criado, Luis Iribarne, 2019, Knowl. Based Syst..

Optimally Storing the User Interaction in Mashup Interfaces Within a Relational Database

James Zijun Wang, Antonio Corral, Javier Criado, 2016, ICWE Workshops.

CompareML: A Novel Approach to Supporting Preliminary Data Analysis Decision Making

Alvaro E. Prieto, Juan Carlos Preciado, Fernando Sánchez-Figueroa, 2021 .

A Real-Life Machine Learning Experience for Predicting University Dropout at Different Stages Using Academic Data

José María Conejero, Juan Carlos Preciado, Fernando Sánchez-Figueroa, 2021, IEEE Access.

Towards the use of Data Engineering, Advanced Visualization techniques and Association Rules to support knowledge discovery for public policies

Alvaro E. Prieto, José María Conejero, Juan Carlos Preciado, 2021, Expert Syst. Appl..