International Journal of Machine Learning and Cybernetics

Special Issue on Machine Learning and Computational Intelligence in Big Data

Call for papers

Big Data consist of the basis of future data driven decision making techniques. Big Data as a research area has attracted the attention of many research institutes and companies worldwide. The reason is that, in many applications domains, huge amount of data are produced and stored requiring for the appropriate management mechanisms to have the so called Big Data analytics services. The increase on the user devices lead to an increased amount of data as well as an increased number of (multidimensional, spatio-temporal) queries over the discussed large amounts of data. The appropriate management of huge amounts of structured as well as unstructured data is the key issue for future research. Decision makers should adopt intelligent techniques over Big Data analytics for reaching efficient and time-optimized decisions according to the application domain.
The adoption of Machine Learning (ML) and Computational Intelligence (CI) methods and theories in handling Big Data could offer a number of advantages. Both ML and CI could provide means for the creation of intelligent systems that will respond to user / application queries in the minimum time together with the highest possible performance. The main focus of this special issue will be on the adoption of ML and CI methods and theories in the Big Data research domain. Contributors will have the opportunity to present novel methods, theories, tools, techniques and methodologies that adopt ML and CI. This special issue will record recent developments in the discussed field. Topics of interest include, but are not limited to:

• Machine Learning algorithms over Big Data
• Intelligent decision making systems for Big Data
• Classification and regression methods for Big Data
• Supervised, Unsupervised learning for Big Data
• Large Scale Graph mining and Learning for Big Data
• Optimization techniques in Big Data applications
• Prediction methods for Big Data applications
• Handling real-time, distributed large scale data
• Evolutionary computing in Big Data
• Neural networks in Big Data applications
• Swarm Intelligence and Big data
• Handling uncertainty in Big Data
• Applications of Fuzzy Set theory in Big Data
• Big Data applications (social networks, bio-, life sciences datasets, etc)
• Curating and Discovering Data

Before submission authors should carefully read the instruction to authors which is available at http://www.springer.com/engineering/computational+intelligence+and+complexity/journal/13042. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at https://www.editorialmanager.com/jmlc/ selecting SI: Machine Learning and Computational Intelligence in Big Data in the article type field.

Important dates are:

Manuscript due October 31st, 2014
Authors’ Notification December 31st, 2014
Final Submission January 31st, 2015
Publication Date 2015

Guest Editors

Dr Anagnostopoulos, Christos
School of Computing Science
University of Glasgow
G12 8QQ
Glasgow, UK
e-mail: christos.anagnostopoulos@glasgow.ac.uk

Dr Kolomvatsos, Kostas
Department of Computer Science
University of Thessaly
Lamia, 35100
Greece
e-mails: kostasks@di.uoa.gr, kolomvatsos@cs.uth.gr

Published by Springer (http://www.springer.com)

http://www.springer.com/journal/13042
International Journal of Machine Learning and Cybernetics
Editors-in-Chief: X.-Z. Wang, D. S. Yeung
ISSN: 1868-8071 (print version)
ISSN: 1868-808X (electronic version)
Journal No. 13042