41st Annual Conference of the
IEEE Industrial Electronics
Society IECON’15
9-12 November 2015, Yokohama, Japan
Special Session on
“Big Data Analytics for Industrial Informatics”
organized by
Principal Organizer: Prof Elizabeth Chang
(Elizabeth.chang@unsw.edu.au)
Affiliation: University of New South Wales and Australian Defence Force
Academy (UNSW@ADFA), Australia
Professor Paulo Leitao (pleitao@ipb.pt)
Polytechnic Institute of Bragança, 5301-857 Bragança, Portugal
Prof Tharam Dillon (T.Dillon@adfa.edu.au)
University of New South Wales and Australian Defence Force Academy
(UNSW@ADFA) Australia
Dr. Farookh Khadeer Hussain (farookh.hussain@uts.edu.au) University
Technology Sydney, Sydney Australia
Call for Papers
Big data analytics is concerned with the process of analysing very large volumes of
data from heterogeneous sources. It leverages the use of various methods such as
(but not limited to), conjoint data mining, finding correlations and (hidden) patterns
through intelligent computational intelligent technologies, and various statistical
analysis methods. Given the large volume of data and the 5V of big data (volume,
veracity, variety, velocity and value) of big data, there is need for further research
work in cutting advanced techniques for analysing large data sets. This problem
assumes particular importance in an industrial or enterprise context. The aim of this
special session is to foster discussions amongst various experts working in this area.
Other research dimensions of analysing large data sets include modelling the impact
on the existing heterogeneous distributed multi-platforms for industrial applications
and the challenge of meeting the data quality requirements, real-time data
intelligence and strategic decision making for industrial applications.
Innovative research contributions covering the area of big data analytics, techniques,
methods and tools and their applications to various industrial applications, are invited
to submit to this special section but are not limited to:
• Conjoint Data, text and content mining
• Conjoint Data mining for Complex data structures including trees, graphs, text
and spatial-temporal data
• Conjoint data mining for Mixed information types including image, video, web
and text
• Data Mining for data that is distributed across multiple heterogeneous data
sources
• Joint mining of structured, semi-structured and unstructured information
• Visualisation and mining of semi-structured information
• Stream Data Mining
• Mining of workflow, process mining, and rare events and frequently occurring
events
• Web mining and document management
• Data mining for data quality and data cleansing
• Integrating a knowledge base from a data mining system and applying this
knowledge during the data mining
• Integrating a wide range of data mining techniques and methods and
deriving incremental new knowledge from large data sets and prior knowledge
Submission procedure, deadlines, and author instructions:
A manuscript submitted to the Special Session of IECON 2015 must be in the IEEE
double format with single space 10p fonts and figures included in the text, so the
length of the manuscript of 8 pages long in PDF format can be evaluated. For your
convenience you may download the WORD template.doc that will be made available
on the conference website: http://iecon2015.com/
Deadlines:
 Reception of full paper:
 Paper acceptance notification:
 Camera ready paper reception:
April 15, 2015
June 15,2015
August 15, 2015
This Special Session is supported by the IEEE IES Technical Committee on
Industrial Informatics (ieee-tcii.org)
International Reviewers
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Armando Colombo
Omar Hussain
Farookh Khadeer Hussain
Wing-Kuen Ling
Jenny Huang
Ernesto Damiani
Youssef Ibrahim
Paulo Leitao
Paolo Cervalo
Achim Karduck
11.
12.
13.
14.
15.
16.
Vish Ramanokar
Sinan Turmer
Wenny Rahayu
George Fodor
Jaipal Singh
Mukesh Mohania