-------- Forwarded Message --------
*CALL FOR CHAPTER PROPOSALS*
*Proposal Submission Deadline: February 28, 2018*
*Managerial Perspectives on Intelligent Big Data Analytics*
A book edited by Prof. Dr. Zhaohao Sun (PNG University of
Technology, PNG)
https://www.igi-global.com/publish/call-for-papers/call-details/3134
or
http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=72541
Introduction
We are living in an age of trinity: big data, analytics and
artificial
intelligence (AI). Big data, analytics and AI are at the frontier
for
revolutionizing our work, life, business, management and
organization as
well as healthcare, finance, e-commerce and web services.
Intelligent big
data analytics integrating big data, analytics and artificial
intelligence
(AI) is at the core of this age of trinity. It becomes disruptive
technology for healthcare, e-commerce, web services, service
computing,
cloud computing and social networking computing. However, many
fundamental,
technological and managerial issues for developing and applying
intelligent
big data analytics remain open. For example, What are the real big
characteristics of big data? what is the foundation of intelligent
big data
analytics? How should intelligent big data analytics be
classified? What is
Intelligence 2.0? What are the characteristics of the age of
trinity? How
can apply intelligent big data analytics to improve healthcare,
e-commerce,
mobile commerce, web services and digital transformation? What is
the
impact of intelligent big data analytics on business and
management? This
book will address these issues by exploring the cutting-edge
theory,
technologies and methodologies of intelligent big data analytics,
and
emphasize integration of artificial intelligence, business
intelligence,
digital transformation and intelligent big data analytics from a
perspective of computing, service and management. This book also
provides
applications of the proposed theory, technologies and
methodologies of
intelligent big data analytics to e-SMACS (electronic, social,
mobile,
analytics, cloud and service) commerce and service, healthcare,
digital
transformation including the Internet of things, sharing economy,
and
Industry 4.0 in the real world. The proposed approaches will
facilitate
research and development of big data analytics, data science, AI,
intelligent systems, digital transformation, e-business and web
service,
service computing, cloud computing and social computing.
Objective of the book
This book’s primary objective is to convey the foundations,
technologies,
thoughts, and methods of intelligent big data analytics with
applications
to scientists, engineers, educators and university students,
business,
service and management professionals, policy makers and decision
makers and
others who have interest in intelligent big data, analytics, AI,
digital
transformation, e-SMACS computing, commerce and service as well as
data
science.
*Target audience*
Primary audiences for this book are undergraduate, postgraduate
students
and variety of professionals in the fields of big data, data
science,
analytics, AI, computing, commerce, business, services, management
and
government. The secondary audience(s) for this book is the variety
of
readers in the fields of government, consulting, business and
trade as well
as the readers from all the social strata.
Papers as book chapters of all theoretical and technological
approaches,
and applications of intelligent big data analytics for management
are
welcome.
Submissions that cross multiple disciplines such as management,
service,
business, artificial intelligence, intelligent systems, data
science,
optimization, statistics, information systems, decision sciences,
and
industry to develop theory and provide technologies and
applications that
could move theory and practice forward in intelligent data
analytics, are
especially encouraged.
*Recommended topics*
Topics of contributions include foundations, technologies,
applications and
emerging technologies and applications of intelligent big data
analytics as
follows.
*Part I. Foundations of Intelligent Big Data Analytics*
Topics: fundamental concepts, models/architectures,
frameworks/schemes or
foundations for planning, designing, building, operating or
evaluating,
managing intelligent big data analytics. The following topics
might also
include, but not limited to.
· Big Data Science
· Big Data Intelligence
· Intelligent Big Data Analytics as a Science
· Decision Science for Intelligent Big Data Analytics
· Big Data Computing and Foundations
· New Computational Models for Big Data
· Mathematical fundamentals of Intelligent Big Data Analytics
· Fuzzy Logic Approach to Intelligent Big Data Analytics
· Graph theory for Intelligent Big Data Analytics
· ICT fundamentals for Big Data Analytics
· Intelligent Visualization Techniques for Big Data Analytics
· Statistical Modelling for Intelligent Big Data Analytics
· Machine learning for Intelligent Big Data Analytics
· Optimization Techniques for Intelligent Big Data Analytics
· Data Mining for Big Data Analytics
· Business Models for Intelligent Big Data Analytics
· Real-time algorithms for Intelligent Big Data Analytics
· Computing thinking for Intelligent Big Data Analytics
· Computational Foundations of Intelligent Big Data Analytics
· Philosophical Foundations of Intelligent Big Data Analytics
· Managerial Foundations of Intelligent Big Data Analytics
*Part II. Technologies for Intelligent Big Data Analytics*
Topics: Technologies for developing intelligent big data analytics
might
include the following topics, but not limited to.
· Intelligent Big Data Analytics as a Technology
· Intelligent Big Data Analytics as a Service
· Rule-based Systems,
· Machine Learning Techniques,
· Multi-agent Systems Techniques,
· Neural Networks Systems,
· Fuzzy Logic Systems,
· Cased-based Reasoning Techniques,
· Genetic Algorithms Techniques,
· Data Mining Algorithms,
· Cognitive Computing,
· Natural Computing,
· Intelligent Agents,
· Intelligent User Interfaces,
· Web Technologies,
· Intelligent Big Data Technologies,
· Intelligent Service Technologies,
· Social Networking Technologies,
· Intelligent Decision Making Technologies,
· Intelligent DSS Technologies,
· Intelligent Management Technologies and Business Technologies.
*Part III. Applications of Intelligent Big Data Analytics*
Topics: cases and applications for using foundations and
technologies in
Part I, II for planning, designing, building, managing and
operating or
evaluating of intelligent big data analytics in the various
domains such as
data science, digital transformation, SMACS computing, commerce
and
services, financial services, legal services, healthcare services,
educational services, and military services taking into account
intelligent
big data diagnostic, descriptive, predictive and prescriptive
analytics .
The following topics might also include, but not limited to.
· Intelligent Big Data Analytics and Intelligence with
applications,
· Intelligent Big Data Analytics Based Services Innovation,
· Intelligent Big Data Analytics in Business Ecosystems,
· Intelligent Big Data Analytics with Public and Open Big Data,
· Intelligent Big Data Analytics and Data Markets,
· Intelligent Big Data Analytics for e-Commerce,
· Intelligent Big Data Analytics in Decision Making,
· Intelligent Big Data Analytics in Healthcare,
· Intelligent Big Data Analytics in Banking Industry,
· Intelligent Big Data Analytics in (Online) Social Networking
Services,
· Intelligent Visualization Analytics for Big Data ,
· Security and privacy issues in Intelligent Big Data Analytics,
· Big Data Processing and Management
· Big Data Analytics for Risk Management.
*Part IV. Emerging Technologies and Applications for Intelligent
Big Data
Analytics*
Topics: Emerging technologies, methodologies, and applications for
intelligent big data analytics. The following topics might also
include,
but not limited to
· Emergent AI-based technologies,
· Challenges for Big Data Intelligence,
· Challenges for Intelligent Big Data Analytics Research,
· Challenges for Intelligent Big Data Analytics Applications,
· Challenges for Intelligent Big Data Analytics Tools,
· Managerial Issues for Intelligent Big Data Analytics.
Submission procedure
Researchers and practitioners are invited to submit on or before
February
28, 2018, a chapter proposal of about 1,000 words clearly
explaining the
mission and concerns of his or her proposed chapter. Authors will
be
notified by March 15, 2018 about the status of their proposals and
sent
chapter guidelines. Full chapters are expected to be submitted by
April 30,
2014, and all interested authors must consult the guidelines for
manuscript
submissions at
http://www.igi-global.com/publish/contributor-resources/
before-you-write/ prior to submission. All submitted chapters will
be
reviewed on a double-blind review basis. Contributors may also be
requested
to serve as reviewers for this project.
Note: There are no submission or acceptance fees for manuscripts
submitted
to this book publication, Trust in Knowledge Management and
Systems in
Organizations. All manuscripts are accepted based on a
double-blind peer
review editorial process.
All proposals should be submitted through the eEditorial
Discovery®TM
online submission manager at
http://www.igi-global.com/submission.
Publisher
This book is scheduled to be published by IGI Global (formerly
Idea Group
Inc.), publisher of the "Information Science Reference" (formerly
Idea
Group Reference), "Medical Information Science Reference,"
"Business
Science Reference," and "Engineering Science Reference" imprints.
For
additional information regarding the publisher, please visit
www.igi-global.com. This book is anticipated to be released in
early 2019.
Important Dates
· Proposal due date: February 28, 2018,
· Notification of book proposal assessment: March 15, 2018,
· Full chapter due date: April 30, 2018,
· Notification of editorial results: May 30, 2018,
· Final Submission due date: June 30, 2018.
Inquiries
If you any inquiries about the submission of book chapters, please
do not
hesitate to contact
Prof. Dr. Zhaohao Sun, Ph.D. at
zhaohao.sun@gmail.com
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