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SCI2S Publications (S. Río)

Number of Results: 17

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In Press (2)


2016 (2)

  • [2092] A. Fernandez, S. Río, F. Herrera. Sistemas de Clasificación Basados en Reglas Difusas para Big Data con MapReduce: Análisis de la Granularidad. XVIII Congreso Español sobre Tecnologías y Lógica Fuzzy. ESTYLF 2016, San Sebastián (Spain), 1-2, May 25-27, 2016.
  • [2095] A. Fernandez, S. Río, F. Herrera. A First Approach in Evolutionary Fuzzy Systems based on the Lateral Tuning of the Linguistic Labels for Big Data Classification. 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), Vancouver (Canada), 1-8, July 24-29, 2016.


2015 (8)

  • [1734] V. López, S. Río, J.M. Benítez, F. Herrera. Cost-Sensitive Linguistic Fuzzy Rule Based Classification Systems under the MapReduce Framework for Imbalanced Big Data. Fuzzy Sets and Systems 258 (2015) 5-38. doi: 10.1016/j.fss.2014.01.015 PDF Icon
  • [1860] S. Río, V. López, J.M. Benítez, F. Herrera. A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules. International Journal of Computational Intelligence Systems 8:3 (2015) 422-437. doi: 10.1080/18756891.2015.1017377 PDF Icon
  • [1926] I. Triguero, S. Río, V. López, J. Bacardit, J.M. Benítez, F. Herrera. ROSEFW-RF: The winner algorithm for the ECBDL'14 Big Data Competition: An extremely imbalanced big data bioinformatics problem. Knowledge-Based Systems 87 (2015) 69-79. doi: 10.1016/j.knosys.2015.05.027 PDF Icon
  • [1939] D. Peralta, S. Río, S. Ramírez-Gallego, I. Triguero, J.M. Benítez, F. Herrera. Evolutionary Feature Selection for Big Data Classification: A MapReduce Approach. Mathematical Problems in Engineering, vol. 2015, Article ID 246139 (2015) 11 pages. doi: 10.1155/2015/246139
  • [1951] D. Galpert, S. Río, F. Herrera, E. Ancede, A. Antunes, G. Agüero-Chapin. An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species. BioMed Research International (2015) 12 pages, Article Id 748681. doi: 10.1155/2015/748681 PDF Icon
  • [1952] S. Río, J.M. Benítez, F. Herrera. Analysis of Data Preprocessing Increasing the Oversampling Ratio for Extremely Imbalanced Big Data Classification. The 9th IEEE International Conference on Big Data Science and Engineering(IEEE BigDataSE-15), Helsinki, Finland, 20-22 August, 2015. PDF Icon
  • [1988] S. Río, J.M. Benítez, F. Herrera. Preprocesamiento de Datos mediante el Incremento de la Tasa de Sobremuestreo para Problemas de Big Data Extremadamente Desbalanceados. XVI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2015), Albacete (Spain), 10 pages, 9-12 November, 2015. PDF Icon
  • [2069] D. Galpert, S. Río, F. Herrera, E. Ancede, A. Antunes, G. Agüero-Chapin. Pairwise Ortholog Detection in Related Yeast Species by Using Big Data Supervised Classifications. MOL2NET, the 1st International Conference on Multidisciplinary Sciences, Sciforum Electronic Conference Series, Vol. 1, 1-10, December 5–15, 2015. doi: 10.3390/MOL2NET-1-e002 PDF Icon


2014 (3)


2013 (1)

  • [1705] S. Río, V. López, J.M. Benítez, F. Herrera. Aplicando Métodos de Aprendizaje Sensible al Coste para Mejorar Problemas de Big Data Extremadamente Desbalanceados Usando Random Forest. IV Congreso Español de Informática (CEDI 2013). XV Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2013), Madrid (Spain), pp. 109-118, 17-20 September, 2013. PDF Icon


2012 (1)

  • [1545] A. Fernandez, S. Río, F. Herrera, J.M. Benítez. An Overview on the Structure and Applications for Business Intelligence and Data Mining in Cloud Computing. 7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing (KMO'12), Salamanca (Spain), pp. 559-570, 11-13 July 2012. PDF Icon