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Título : A view on Fuzzy Systems for big data: progress and opportunities
Autor : Fernández, Alberto .
Carmona del Jesús, Cristóbal José
Jesus, María José del .
Herrera, Francisco .
Publicado en: Publication Cover International Journal of Computational Intelligence Systems. 2016, V. 9, supl. 1, p. 69-80
Editorial : Atlantis Press
Fecha de publicación : abr-2016
ISSN : 1875-6891
DOI: 10.1080/18756891.2016.1180820
Resumen : Currently, we are witnessing a growing trend in the study and application of problems in the framework of Big Data. This is mainly due to the great advantages which come from the knowledge extraction from a high volume of information. For this reason, we observe a migration of the standard Data Mining systems towards a new functional paradigm that allows at working with Big Data. By means of the MapReduce model and its different extensions, scalability can be successfully addressed, while maintaining a good fault tolerance during the execution of the algorithms. Among the different approaches used in Data Mining, those models based on fuzzy systems stand out for many applications. Among their advantages, we must stress the use of a representation close to the natural language. Additionally, they use an inference model that allows a good adaptation to different scenarios, especially those with a given degree of uncertainty. Despite the success of this type of systems, their migration to the Big Data environment in the different learning areas is at a preliminary stage yet. In this paper, we will carry out an overview of the main existing proposals on the topic, analyzing the design of these models. Additionally, we will discuss those problems related to the data distribution and parallelization of the current algorithms, and also its relationship with the fuzzy representation of the information. Finally, we will provide our view on the expectations for the future in this framework according to the design of those methods based on fuzzy sets, as well as the open challenges on the topic
Palabras clave: Big Data
Fuzzy Rule Based Classification Systems,
Licencia: https://creativecommons.org/licenses/by-nc/4.0/
URI : http://hdl.handle.net/10259/4794
Versión del editor: https://doi.org/10.1080/18756891.2016.1180820
Aparece en las colecciones: Artículos GICAP

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