RT info:eu-repo/semantics/article
T1 A view on Fuzzy Systems for big data: progress and opportunities
A1 Fernández, Alberto .
A1 Carmona del Jesús, Cristóbal José
A1 Jesus, María José del .
A1 Herrera, Francisco .
K1 Big Data
K1 Fuzzy Rule Based Classification Systems,
K1 Clustering
K1 MapReduce
K1 Hadoop
K1 Spark
K1 Flink
AB Currently, we are witnessing a growing trend in the study and application of problems in the framework ofBig Data. This is mainly due to the great advantages which come from the knowledge extraction from ahigh volume of information. For this reason, we observe a migration of the standard Data Mining systemstowards a new functional paradigm that allows at working with Big Data. By means of the MapReducemodel and its different extensions, scalability can be successfully addressed, while maintaining a goodfault 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, wemust stress the use of a representation close to the natural language. Additionally, they use an inferencemodel 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 thedifferent learning areas is at a preliminary stage yet. In this paper, we will carry out an overview of themain existing proposals on the topic, analyzing the design of these models. Additionally, we will discussthose problems related to the data distribution and parallelization of the current algorithms, and also itsrelationship with the fuzzy representation of the information. Finally, we will provide our view on theexpectations for the future in this framework according to the design of those methods based on fuzzysets, as well as the open challenges on the topic
PB Atlantis Press
SN 1875-6891
YR 2016
FD 2016-04
LK http://hdl.handle.net/10259/4794
UL http://hdl.handle.net/10259/4794
LA eng
NO Spanish Ministry of Science and Technology underproject TIN2014-57251-P; the Andalusian ResearchPlan P11-TIC-7765; and both the Universityof Ja´en and Caja Rural Provincial de Ja´en underproject UJA2014/06/15.
DS Repositorio Institucional de la Universidad de Burgos
RD 24-abr-2024