Special Issue of the Journal of New Mathematics & Natural Computing

Big Data Analytics: Fundamentals and applications

The Journal of New Mathematics & Natural Computing is published by World Scientific Publishing (http://www.worldscientific.com/worldscinet/nmnc) with ISSN:1793-0057 [print] and ISSN:1793-7027 [electronic]. This journal is covered in Cabell’s Computer Science directory, abstracted and indexed in Scopus, Mathematical Reviews, Zentralblatt MATH, RePEC, and listed by ERA Australia.

Big Data Analytics has been drawing increasing attention in academia of computer science, information technology, mathematics, business, management and industry of healthcare, medical science. Big Data Analytics is an emerging science and technology armed by thoroughly multidisciplinary advancement of information and communication technology (ICT), mathematics, operations research (OR), and decision sciences for big data. The main components of Big Data Analytics include descriptive analytics, predictive analytics and prescriptive analytics, which correspondingly address the three questions in related to big data: when and what happened? What is likely to happen? And what should happen with the best outcome under uncertainty? All these questions are often encountered in almost every part of science, technology, business, management, organization and industry. Mathematics, optimization, machine learning, data mining, cloud computing, statistical modelling, as well as visualization technology, to name a few, are proved fundamentals for research and development of Big Data Analytics.

1 Objective and topics

The objective of this Special Issue in Journal of New Mathematics and Natural Computing is to present the current state of art research and practical experiences on Big Data Analytics from a viewpoint of mathematics, statistics, graph theory, optimization, ICT, intelligent systems, machine learning, decision science and economics and beyond.

Topics of interest include, but are not limited to, the following:

1. Fundamentals of Big Data Analytics

* Big Data Analytics  as a science

* Big Data Analytics  as a technology

* Big Data Analytics  as a service

* Big Data Science and Foundations

* New Computational Models for Big Data

* Mathematical fundamentals of Big Data Analytics

* Graph theory for Big Data Analytics

* ICT  fundamentals for Big Data Analytics

* Visualization techniques for Big Data Analytics

* Decision science for Big Data Analytics

* Statistical modelling for Big Data Analytics

* Machine learning for Big Data Analytics

* Optimization techniques for Big Data Analytics

* Research methodology for Big Data Analytics

* Data mining for Big Data Analytics

* Business models  for Big Data Analytics

* Real-time algorithms for  Big Data Analytics

* Statistical thinking and computing thinking for Big Data Analytics

2. Applications of Big Data Analytics

* Big Data Analytics based services innovation

* Big Data Analytics in business ecosystems

* Big Data Analytics with public and open data

* Big Data Analytics and data markets

* Big Data Analytics for e-commerce

* Big Data Analytics for web services

* Big Data Analytics in business decision making

* Big Data Analytics in healthcare

* Big Data Analytics in banking industry

* Big Data Analytics in social networking services

* Visualization Analytics for Big Data

* Big Data Search and Mining

* Big Data Security & Privacy

* Big Data processing and management

* Big Data analytics for risk management

     3.    Challenges on Big Data Analytics

1. Challenges for Big Data Analytics research

2. Challenges for Big Data Analytics applications

3. Challenges for Big Data Analytics tools

4. Challenges for Big Data Analytics methodologies

2  Notes for Intending Authors

We are seeking original, genuine, innovative, scientifically rigorous research papers on fundamentals and applications of Big Data Analytics. Empirical research, case studies or theory based qualitative and quantitative studies on Big Data Analytics are also welcome.

Author guidelines can be found at: http://www.worldscinet.com/style_files/nmnc/202-readme_2e.shtml. All submissions will be refereed by at least three reviewers. Submissions should be directed by email to z.sun@federation.edu.au, zhaohao.sun@gmail.com and ppw@ee.duke.edu

3  Important dates

* Full paper submission: April 30, 2015

* Notification of acceptance: July 15, 2015

* Revised submission: August  20, 2015

* Final acceptance notification: September 20, 2015

* Camera ready version of paper: November 20, 2015

* Publication: January – May, 2016

4 Editors

Associate Prof. Dr Zhaohao Sun, Ph.D.

Department of Business Studies, PNG University of Technology, Lae, PNG, &

Honorary Senior Research Fellow

School of Engineering and Information Technology, Federation University Australia, Ballarat, AUSTRALIA

Email: z.sun@federation.edu.au, or zhaohao.sun@gmail.com