Workshop:
Intelligent Big
Data Analytics and Services (ItBDAS)
Realizing intelligent services are the eternal aims of researchers,
enterprises and governments. Big data is an emerging paradigm applied to
datasets whose size is beyond the ability of commonly used software tools to
capture, manage, and process the data within a tolerable elapsed time. It provides more
opportunities for providing intelligent services based on big data analytics.
Big data technologies in industry services and everyday life have led to the
emergent and data-focused economy stemming from many aspects of industrial
applications. The rich and vast services are creating unprecedented research
opportunities in diverse industrial fields such as public health, urban
studies, economics, finance, geography and social sciences.
Big data services are deployed in a multi-scale complex distributed architecture. They can further formulate a high-level computational intelligence which is based on emerging analytical techniques such as big data analytics. Computational
intelligence employs many existing software tools from advanced analytics disciplines such as natural language processing, machine learning, data mining and predictive
analytics. Computational intelligence also becomes increasingly important to anticipate technical and practical
challenges and to identify best practices learned through experience.
This workshop aims to presenting novel theories, technologies and solutions to challenging technical issues as well as the compelling industrial systems. This workshop will share research works and related practical experiences to benefit the participants of intelligent
big data analytics and services. This will verify that big data
services are playing an important role in supporting computational intelligence for the industry systems. It has also established a new
cross-discipline research topic in computer science, information science and
industry engineering. The workshop solicits novel papers on a broad range of
topics including but not limited to:
·
Novel theoretical and
computational models for big data analytics and services
·
Big data analysis
and visualization for intelligent information services
·
Knowledge and
information organization theory and technology for big data analytics and services
·
Requirement
engineering of big data services for computational intelligence
·
Interoperability of
heterogeneous big data services for computational intelligence
·
Big data services
such as massive data analysis and mobile analysis
·
Big data services
processing in industrial networks and industrial wireless sensor networks
·
Multi-tenant business
process
·
Big data analytics and services in medical and healthcare
·
On-demand big data
services selection, composition, and provisioning for computational
intelligence
·
Context-aware big
data service management and processing for computational intelligence
·
Scalable and
efficient architectures and algorithms of big data services for computational
intelligence
·
Multiple
source data processing and integration for big data analytics
·
Security and privacy
issues on big data analytics and services
·
Industrial
application of big data services for computational intelligence
Important Dates:
Submission due: May 6, 2015
Notification: May 20, 2015
Camera Ready: June 5, 2015
Program Co-chairs:
Junsheng Zhang, Institute of Scientific and Technical Information of China,
China
Yunchuan Sun, Beijing Normal University, China
Program Committee:
Jin Liu, Wuhan University, China
Shanghui Liu, China Medical University, China
Peng Qu, Institute of Scientific
and Technical Information of China, China
Yiying Zhang,State Grid Information & Telecommunication Branch,
China
Wen Zeng, Institute of
Scientific and Technical Information of China, China
Dongling Chen, Shenyang University, China
Paper Submission:
https://easychair.org/conferences/?conf=atc2015
Select
the track “ItBDAS”
Publication:
Accepted workshop papers will
be included in the proceedings published by IEEE-CS Conference Publishing
Services (submitted to the IEEE-DL and EI index).