This event is endorsed
and organized by

EAI International Conference on Computer Science and Engineering

November 3–4, 2017 | Bangkok, Thailand


― Call for Papers ―

Special Session


Optimization Techniques in Smart Data and Visualization (OSDV)



At the event of the Second EAI International Conference on Computer Science and Engineering (COMPSE) in Bangkok Thailand, at November 3-4, 2017 (, we invite submissions of papers to a Special Session on Optimization Techniques in Smart Data and Visualization. Immensely massive amounts of data are now and lawfully available on the Web. This data is generally heterogeneous and merely structured. Data mining and Machine learning models, which have developed to automatically retrieve, transfer or cluster observations on exceedingly immense yet homogeneous data collections have to be thought. Indeed, many problems, ineluctably associated to Big voluminous Data, have manifested for tradeoffs between the two conflicting goals of speed and precision. This has led to some recent initiatives in both theory, practice, and has highly incentivized the interest of the Machine Learning community. Further theoretical challenges include how to tackle problem difficulties with various target classes, apt optimization techniques to smart data dilemmas. Structured/sequential prediction models for smart data problems such as predictions also gained importance in recent years.
With our Special Session at COMPSE 2017, we aim to foster the collaboration in the intersection between the fields of Smart Data handling and Optimization techniques to represent state-of-the-art Big Data to Smart Data contributions as going to be present and discussed at COMPSE 2017. Herewith, the Session Organizers wish to encourage excellent research and interaction in the vibrant fields of modern computing. This special session pursues solutions on interdisciplinary gaps between data and intelligent approaches.
This OSDV session focuses on important issues and inter-dependent domains in which intelligent optimization techniques in Smart cities. Visualizations in Smart Data (SD) must be intuitive and must support an interactive, collaborative discovery process, data analysis. Smart data are rapidly increasing with respect of size, dimensionality and complexity. On the one hand, big and streaming data sets are becoming more and more popular in complex systems such as industrial manufacturing processes, surveillance, finance, smart cities, sensor networks, or health-care. On the other hand, the dimensionality of data can easily reach a few thousand and data sources are often enriched by additional information, which gives crucial clues to avoid timely. These facts demand for advanced methods and tools, which can cope with these big and complex data with respect to not only its sheer size, but also its often-challenging mathematical, statistical properties such as heterogeneous quality, data trends, presence of sporadic events, and necessity for strong regularization.
A selection of the best papers will be recommended for publication in special issues of scientific journals, or as an edited book.

Topics of interest: but not limited to

 Intelligent Transportation systems
 Smart QR Applications
 Big data analytics
 Big data visualization
 Big data Open Data in Smart cities
 Machine learning for Streaming data
 Artificial Intelligence, advanced algorithms, machine learning
 Smart Intelligent traffic control Centers
 Optimization techniques for large-scale data
 Big data structures prediction models
 Optimization techniques for Smart Data
 Education and Health in Smart city
 Business Intelligence Data Analytics
 Industrial Challenges in Intelligent Data Mining.
 Healthcare Data Visualization
 Computational steering for long-running data mining applications

Session Chair: Dr. J. Joshua Thomas, KDU PENANG University College, Malaysia


Important Dates

Full paper/Poster/Demo/workshop paper Submission deadline: 30th July 2017
Notification deadline: 20th September 2017
Camera-ready deadline: 15th October 2017



Papers should be submitted via Confy system. Please follow instructions on initial submission and in author’s kit when submitting your paper.
For closer details please cf.
Dr. J. Joshua Thomas
Department of Computing
School of Engineering, Computing and Built Environment
KDU PENANG University College, Malaysia
32, Anson Road, George Town,
10400, Penang Malaysia