![Foto de DIEGO JESÚS](/img/uploaded/14163A1B07B82AB8E8802557A860445F.png)
DIEGO JESÚS
GARCÍA GIL
PROF. AYUDANTE DOCTOR
Publications (15) Publications de DIEGO JESÚS GARCÍA GIL
2024
-
Smart Data Driven Decision Trees Ensemble Methodology for Imbalanced Big Data
Cognitive Computation, Vol. 16, Núm. 4, pp. 1572-1588
2023
-
Fusing anomaly detection with false positive mitigation methodology for predictive maintenance under multivariate time series
Information Fusion, Vol. 100
-
Multi-step histogram based outlier scores for unsupervised anomaly detection: ArcelorMittal engineering dataset case of study
Neurocomputing, Vol. 544
2021
-
Anomaly detection in predictive maintenance: A new evaluation framework for temporal unsupervised anomaly detection algorithms
Neurocomputing, Vol. 462, pp. 440-452
2020
-
Big Data Preprocessing: Enabling Smart Data
Springer International Publishing, pp. 1-186
2019
-
A first approach on big data missing values imputation
IoTBDS 2019 - Proceedings of the 4th International Conference on Internet of Things, Big Data and Security
-
Big data preprocessing as the bridge between big data and smart data: Bigdapspark and Bigdapflink libraries
IoTBDS 2019 - Proceedings of the 4th International Conference on Internet of Things, Big Data and Security
-
Enabling Smart Data: Noise filtering in Big Data classification
Information Sciences, Vol. 479, pp. 135-152
-
From Big to Smart Data: Iterative ensemble filter for noise filtering in Big Data classification
International Journal of Intelligent Systems, Vol. 34, Núm. 12, pp. 3260-3274
-
Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol. 9, Núm. 2
2018
-
Bagging-RandomMiner: un algoritmo en mapreduce para detección de anomalías en big data
XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España
-
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems
Knowledge-Based Systems, Vol. 153, pp. 176-192
-
On the use of random discretization and dimensionality reduction in ensembles for big data
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
-
Principal Components Analysis Random Discretization Ensemble for Big Data
Knowledge-Based Systems, Vol. 150, pp. 166-174
-
Smart Data: Filtrado de Ruido para Big Data
XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España