February 2nd, 2018 
Daniela Lopez de Luise *********************************************************************
Berkeley Initiative in Soft Computing (BISC)
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*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)
or
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,
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