In recent years, with advances in technology in various areas such as sensors, communications, internet or databases, the amount of data being generated and stored is increasing, to the extent that 90% of the world's data has been generated in recent years. This large amount of data and the technologies that process it is the area known as "big data". Today, the analysis and interpretation of large volumes of data represent a fundamental need for the extraction of useful and valuable knowledge for our socio-economic environment.

The development of tools capable of processing the data and providing an associated value arises from Google's MapReduce paradigm, and its implementation in open source, Hadoop. Many other tools have been developed to address the limitations of this paradigm. As an example, the Apache Spark platform is a new system for the development of algorithms that use memory processing faster than Hadoop processing and without its limitations in iterative processes.

With the BigDADE workshop, we want to encourage the participation of researchers working in the field of data mining, who have focused their attention on the scalability of learning algorithms as well as on the development of proposals focused on Big Data technologies, both algorithmic and applied. It will be an opportunity to present results and exchange ideas about this line of research, both from experts in the field and from those interested in approaching it.



Granada está indefensa ante la gente; pues ante los halagos nada ni nadie tiene manera de defenderse - Federico García Lorca


Topics of interest for this Workshop include (but are not limited to) the following:

  • Scalable knowledge discovery
  • Scalability and efficiency in data analytics
  • Visualization for Big Data
  • Big Data Knowledge Discovery
  • Grading algorithms for Big Data
  • Clustering algorithms for Big Data
  • Association rules extraction algorithms for Big Data
  • Algorithms for mass data flow in Big Data
  • Social Network Data Analysis with Big Data Technology
  • Deep Learning
  • Tools for knowledge extraction in Big Data
  • Computational Intelligence in Analytics Big Data
  • Treatment of Big Data Analytics Uncertainty
  • Big Data Analytics and Cloud Computing
  • Applications in Big Data Analytics: security, medicine, bioinformatics, social networks, industry, teaching, etc.

Program Committee

Amparo Alonso BetanzosUniversidade da Coruña
Jaume BacarditNewcastle University
Antonio BahamondeUniversity of Oviedo
José Manuel BenítezUniversity of Granada
Concha BielzaTechnical University of Madrid
Verónica BolónUniversidade da Coruña
David CamachoAutonomous University of Madrid
Andrés CanoUniversity of Granada
Emilio CorchadoUniversity of Salamanca
Oscar CordónUniversity of Granada
Juan José del CozUniversity of Oviedo
María José del JesusUniversity of Jáen
Javier del SerTecnalia
José DorronsoroAutonomous University of Madrid
Anibal FigueirasCarlos III University of Madrid
Mikel GalarPublic University of Navarra
José A. GámezUniversity of Castilla la Mancha
Salvador GarcíaUniversity of Granada
Cesar García-OsorioUniversity of Burgos
Nicolás García-PedrajasUniversity of Córdoba
Manuel Gómez-OlmedoUniversity of Granada
Pedro GonzálezUniversity of Jaén
Bertha GuijarroUniversidade da Coruña
Francisco HerreraUniversity of Granada
Pedro LarrañagaTechnical University of Madrid
Victoria LópezUniversidad Complutense de Madrid
José Antonio LozanoUniversity of the Basque Country
David MartínezUniversity College of London
Antonio PeregrínUniversity of Huelva
José M. PuertaUniversity of Castilla la Mancha
José RiquelmeUniversity of Sevilla
Antonio Jesús RiveraUniversity of Jaén
Antonio SalmerónUniversity of Almería
Isaac TrigueroGent University
Alicia TroncosoPablo de Olavide University
Sebastián VenturaUniversity of Córdoba

Submission & formatting

Instructions on the type of work, its preparation and dispatch via the EasyChair platform are the same as for the rest of the conference and can be found at CfP CAEPIA.

Waiting for your contributions for BigDADE 2018!

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