María Martínez Ballesteros
2019
Analysis of the evolution of the Spanish labour market through unsupervised learning Artículo de revista
En: IEEE Access, 2019, (JCR (2018) 4.098).
External Clustering Validity Index based on chi-squared statistical test Artículo de revista
En: Information Sciences, 2019, (JCR(2017): 4,305).
2018
MRQAR: a generic MapReduce framework to discover Quantitative Association Rules in Big Data problems Artículo de revista
En: Knowledge-Based System, vol. 53, no 1, pp. 176-192, 2018, (JCR (2016): 4.529).
2017
Machine learning techniques to discover genes with Potential Prognosis Role in Alzheimer's Disease using different biological sources Artículo de revista
En: Information Fusion, vol. 36, pp. 114-129, 2017, (JCR (2015): 4.353, Q1).
2016
Improving a multi-objective evolutionary algorithm to discover quantitative association rules Artículo de revista
En: Knowledge and Information Systems, vol. 49, no 2, pp. 481-509, 2016, (JCR (2016): 2.004).
Obtaining optimal quality measures for quantitative association rules Artículo de revista
En: Neurocomputing, vol. 176, pp. 36-47, 2016, (JCR (2016): 3.317, Q1).
A Study of the Suitability of Autoencoders for Preprocessing Data in Breast Cancer Experimentation Artículo de revista
En: Journal of Biomedical Informatics, vol. 72, no C, pp. 33-44, 2016, (JCR (2016): 2.753).
2015
Enhancing the scalability of evolutionary algorithms to discover quantitative association rules in large-scale datasets Artículo de revista
En: Integrated Computer-Aided Engineering, vol. 22, no 1, pp. 21-39, 2015, (JCR (2015): 4.981, Q1).
2014
Discovering gene association networks by multi-objective evolutionary quantitative association rules Artículo de revista
En: Journal of Computer and Systems Sciences, vol. 89, no 1, pp. 118-136, 2014, (JCR (2014): , Q2).
Discovering quantitative association rules: A novel approach based on evolutionary algorithms Artículo de revista
En: AI Communications, vol. 27, no 2, pp. 153-165, 2014, (JCR (2014): 0.547, Q4).
Selecting the best measures to discover quantitative association rules Artículo de revista
En: Neurocomputing, vol. 126, pp. 3-14, 2014, (JCR (2014): 2.083, Q2).
2011
Evolutionary Association Rules for Total Ozone Content Modeling from Satellite Observations Artículo de revista
En: Chemometrics and Intelligent Laboratory Systems, vol. 109, no 2, pp. 217-227, 2011, (JCR (2011): 1.920, Q1).
An Evolutionary Algorithm to Discover Quantitative Association Rules in Multidimensional Time Series Artículo de revista
En: Soft Computing, vol. 15, no 10, pp. 2065-2084, 2011, (IF 1.880 24/99 Int App Q1, 30/111 Art Int Q2).
2010
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution Artículo de revista
En: Integrated Computer-Aided Engineering, vol. 17, no 3, pp. 227-242, 2010, (JCR (2010): 2.122, Q1).
- mariamartinez@us.es
- +34 954 556 949
- Universidad de Sevilla. ETSII. F1.81