-------- Forwarded Message -------- Subject: [AISWorld] CFP: Managerial Perspectives on Intelligent Big Data Analytics Date: Wed, 14 Feb 2018 14:44:53 +1000 From: Zhaohao Sun zhaohao.sun@gmail.com To: aisworld@lists.aisnet.org, IRMA ListServ irma-l@irma-international.org, BISC-Group bisc-group@eecs.berkeley.edu

*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 _______________________________________________ AISWorld mailing list AISWorld@lists.aisnet.org