| Transforming big data into smart data: An insight on the use of the k‐nearest neighbors algorithm to obtain quality data I Triguero, D García‐Gil, J Maillo, J Luengo, S García, F Herrera Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 9 (2 …, 2019 | 286 | 2019 |
| Enabling smart data: noise filtering in big data classification D García-Gil, J Luengo, S García, F Herrera Information Sciences 479, 135-152, 2019 | 211 | 2019 |
| Big data preprocessing J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera Cham: Springer 1, 1-186, 2020 | 166 | 2020 |
| A comparison on scalability for batch big data processing on Apache Spark and Apache Flink D García-Gil, S Ramírez-Gallego, S García, F Herrera Big Data Analytics 2 (1), 1, 2017 | 149 | 2017 |
| Anomaly detection in predictive maintenance: A new evaluation framework for temporal unsupervised anomaly detection algorithms J Carrasco, D López, I Aguilera-Martos, D García-Gil, I Markova, ... Neurocomputing 462, 440-452, 2021 | 74 | 2021 |
| Principal components analysis random discretization ensemble for big data D García-Gil, S Ramírez-Gallego, S García, F Herrera Knowledge-Based Systems 150, 166-174, 2018 | 52 | 2018 |
| MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems D Martín, M Martínez-Ballesteros, D García-Gil, J Alcalá-Fdez, F Herrera, ... Knowledge-Based Systems 153, 176-192, 2018 | 47 | 2018 |
| From big to smart data: Iterative ensemble filter for noise filtering in big data classification D García‐Gil, F Luque‐Sánchez, J Luengo, S García, F Herrera International Journal of Intelligent Systems 34 (12), 3260-3274, 2019 | 28 | 2019 |
| Multi-step histogram based outlier scores for unsupervised anomaly detection: ArcelorMittal engineering dataset case of study I Aguilera-Martos, M García-Barzana, D García-Gil, J Carrasco, D López, ... Neurocomputing 544, 126228, 2023 | 26 | 2023 |
| Fusing anomaly detection with false positive mitigation methodology for predictive maintenance under multivariate time series D López, I Aguilera-Martos, M García-Barzana, F Herrera, D Garcia-Gil, ... Information Fusion 100, 101957, 2023 | 23 | 2023 |
| DPASF: a flink library for streaming data preprocessing A Alcalde-Barros, D García-Gil, S García, F Herrera Big Data Analytics 4 (1), 4, 2019 | 16 | 2019 |
| Imbalanced data preprocessing for big data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera Big Data Preprocessing: Enabling Smart Data, 147-160, 2020 | 11 | 2020 |
| Smart data driven decision trees ensemble methodology for imbalanced big data D García-Gil, S García, N Xiong, F Herrera Cognitive Computation 16 (4), 1572-1588, 2024 | 8 | 2024 |
| Revolutionizing Sperm Analysis with AI: A Review of Computer-Aided Sperm Analysis Systems FJ Baldán, D García-Gil, C Fernandez-Basso Computation 13 (6), 132, 2025 | 6 | 2025 |
| Data reduction for big data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera Big Data Preprocessing: Enabling Smart Data, 81-99, 2020 | 6 | 2020 |
| Smart data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera Big Data Preprocessing: Enabling Smart Data, 45-51, 2020 | 5 | 2020 |
| RSPCA: Random Sample Partition and Clustering Approximation for ensemble learning of big data MS Mahmud, H Zheng, D Garcia-Gil, S Garcia, JZ Huang Pattern Recognition 161, 111321, 2025 | 4 | 2025 |
| Big data: Technologies and tools J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera Big data preprocessing: Enabling smart data, 15-43, 2020 | 4 | 2020 |
| Dimensionality reduction for big data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera Big Data Preprocessing: Enabling Smart Data, 53-79, 2020 | 4 | 2020 |
| Big data preprocessing as the bridge between big data and smart data: BigDaPSpark and BigDaPFlink libraries DJ García Gil, A Alcalde Barros, J Luengo Martín, S García López, ... SciTePress, 2019 | 4 | 2019 |
Francisco HerreraProfessor Computer Science and AI, DaSCI Research Institute, Granada University, SpainVerified email at decsai.ugr.es
