Publicaciones
A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams,
, Information Fusion, (In Press)
Clustering: An R library to facilitate the analysis and comparison of cluster algorithms,
, Progress in Artificial Intelligence, (In Press)
A case of study with the Clustering R library to measure the quality of cluster algorithms,
, International Conference on Hybrid Artificial Intelligence Systems (HAIS) - Salamanca 5-8 septembre, p.88-97, (2022)
Gamificación mediante juegos de bloques en asignaturas del ámbito de la Inteligencia Artificial en el Grado en Ingeniería Informática,
, VI Congreso Internacional sobre Innovación Pedagógica y Praxis Educativa (INNOVAGOGÍA 2022) - 25 al 27 de mayo, Madrid, (2022)
Uso de metodologías de aprendizaje invertido para resolución de la parte práctica en asignaturas del grado de ingeniería informática,
, XX Congreso Internacional de Investigación Educativa (14-17 de junio), Santiago de Compostela, (2022)
A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams,
, Expert Systems with Applications, Volume 183, Issue C, p.115419, (2021)
2021-Garcia-ESWA.pdf (1.29 MB)

E2PAMEA: un algoritmo evolutivo para la extraccióni eficiente de patrones emergentes difusos en entornos big data,
, Proceedings of the XIX Conference of the Spanish Association for Artificial Intelligence, (2021)
2021 - CAEPIA - E2PM.pdf (173.29 KB)

FEPDS: Una propuesta para la extracción de patrones emergentes difusos en flujos continuos de datos,
, Proceedings of the XIX Conference of the Spanish Association for Artificial Intelligence, (2021)
2021 - CAEPIA - FEPDS.pdf (173.43 KB)

A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns,
, 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020), Volume 1268, p.100, (2020)
2020 - SOCO.pdf (184.72 KB)

E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments,
, Neurocomputing, 11/2020, Volume 415, p.60-73, (2020)
1-s2.0-S0925231220311139-main.pdf (927.85 KB)

FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams,
, IEEE Transactions on Fuzzy Systems, 12/2020, Volume 28, Issue 12, p. 3193-3203, (2020)
09088291.pdf (1.29 MB)

A Big Data Approach for the Extraction of Fuzzy Emerging Patterns,
, Cognitive Computation, 01/2019, Volume 11, p.400–417, (2019)
García-Vico2019_Article_ABigDataApproachForTheExtracti.pdf (1.1 MB)

Study on the use of different quality measures within a multi-objective evolutionary algorithm approach for emerging pattern mining in big data environments,
, Big Data Analytics, Volume 4, Number 1, p.1, (2019)
Subgroup Discovery on Multiple Instance Data,
, International Journal of Computational Intelligence Systems, 12/2019, Volume 12, Issue 2, p.1602-1612, (2019)
125927212.pdf (1.91 MB)

An Overview of Emerging Pattern Mining in Supervised Descriptive Rule Discovery: Taxonomy, Empirical Study, Trends and Prospects,
, WIREs Data Mining and Knowledge Discovery, Volume 8, Issue 1, (2018)
2018-Garcia-Wiley.pdf (728.97 KB)

Improvement of subgroup descriptions in noisy data by detecting exceptions,
, Progress in Artificial Intelligence, Volume 7, Issue 1, p.55-64, (2018)
2017-Gzlez-PRAI.pdf (371.57 KB)

Modelos descriptivos basados en aprendizaje supervisado para el tratamiento de grandes volúmenes de datos y flujos continuos de datos,
, Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), p.1402-1407, (2018)
2018_Garcia_DocConsCAEPIA.pdf (114.01 KB)

MOEA-EFEP: Multi-Objective Evolutionary Algorithm for Extracting Fuzzy Emerging Patterns,
, IEEE Transaction on Fuzzy Systems, Volume 26, Issue 5, p.2861-2872, (2018)
MOEA-EFEP: Un algoritmo evolutivo multi-objetivo para la extracción de patrones emergentes difusos,
, Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), p.671-672, (2018)
2018_Garcia_MAEB.pdf (67.49 KB)

Una primera aproximación para la extracción de patrones emergentes en flujos continuos de datos,
, Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), Mejor trabajo del II Workshop en Big Data y Análisis de Datos Escalable - BigDADE 2018, p.1093-1098, (2018)
2018_Garcia_BigDADE.pdf (129.48 KB)

A First Approach to Handle Emergining Patterns Mining on Big Data Problems: The EvAEFP-Spark Algorithm,
, Proc. of the 2017 IEEE International Conference on Fuzzy Systems, p.1-6, (2017)
2017-Garcia-FuzzIEEE.pdf (383.81 KB)

Análisis de Diferentes Tipos de Reglas en Sistemas Difusos Evolutivos para Minería de Patrones Emergentes,
, Proc. of the XII Spanish Conference on Metaheuristics, Evolutive and Bioinspired Algorithms (MAEB 2017), p.876–885, (2017)
2017-Garcia-MAEB2017.pdf (137.29 KB)

Impact of the Type of Rule in Fuzzy Emerging Pattern Mining on a Big Data Approach,
, Proc. of the II International symposium on Fuzzy and Rough Sets (ISFUROS 2017), (2017)
2017-Garcia-ISFUROS.pdf (317.55 KB)

Analysing Concentrating Photovoltaics Technology through the use of Emerging Pattern Mining,
, Proceedings of the 11th International Conference on Soft Computing Models in Industrial and Environmental Applications, (2016)
2016 - SOCO.pdf (803.02 KB)

Minería de Patrones Emergentes: Una oportunidad para la extracción evolutiva de conocimiento,
, XI Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2016), (2016)
2016-Garcia-EPMReview.pdf (240.75 KB)

Subgroup Discovery with Evolutionary Fuzzy Systems in R: the SDEFSR Package,
, The R Journal, Volume 8, Issue 2, p.307-323, (2016)
2016-Garcia-RJournal.pdf (2.56 MB)

The Influence of Noise on the Evolutionary Fuzzy Systems for Subgroup Discovery,
, Soft Computing, Volume 20, Issue 11, p.4313-4330, (2016)
2016-Luengo-NoiseSD.pdf (972.31 KB)

Análisis descriptivo mediante aprendizaje supervisado basado en patrones emergentes,
, VII Simposio de Teoría y Aplicaciones de Minería de Datos, p.685-694, (2015)
2015 - TAMIDA-a.pdf (251.88 KB)

Usando Algoritmos de Descubrimiento de Subgrupos en R: El Paquete SDR,
, VII Simposio de Teoría y Aplicaciones de Minería de Datos, p.739-748, (2015)
2015 - TAMIDA-b.pdf (335 KB)
