[AISWorld] Call for Chapters: Encyclopedia of Data Science and Machine Learning

[John Wang]

Call for Chapters: Encyclopedia of Data Science and Machine Learning
June 18, 2021:           Proposal Submission Deadline
July 17, 2021:            Notification of Acceptance
Sept. 16, 2021:           Full Chapter Submission

I would like to cordially invite you to consider contributing your expertise to an extremely important book entitled Encyclopedia of Data Science and Machine Learning for the 4th Industrial Revolution. As Editor, I am actively searching for quality material that would be of interest to our audience. This is a wonderful opportunity since contributing authors are generally viewed by others as experts in the sub-field(s) of their chapter content. You can revise, update, and expand your previous contribution(s) because the new encyclopedia covers almost everything.  In addition, you are more than welcome to forward this message to your coauthors, colleagues, research community, Ph.D. students, as well as any scholar(s) who might be interested in participating in this project because we need many contributors from different subareas/perspectives covering its huge topics. More proposals/chapters from an individual or a group are still fine. Please read the following details regarding this forthcoming volume. Thanks.

Sincerely,
John Wang, Professor
Montclair State University, USA

Introduction
Big Data and Machine Learning (BD&ML) are driving the Fourth Industrial Revolution, also referred to as Industry 4.0. With the age of Big Data upon us, we risk drowning in a flood of digital data. Big Data has now become a critical part of the business world and daily life, as the synthesis and synergy of Machine Learning and Big Data has enormous potential. BD&ML will not only maximize the citizens’ wealth, but also promote all society’s health. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, optimization, artificial intelligence, statistics, and the interactions, linkages, and applications of knowledge-based business with information systems. It provides an international forum for practitioners, educators, and researchers to advance the knowledge and practice of all facets of BD&ML, emphasizing emerging theories, principles, models, processes, and applications to inspire and circulate cutting-edge findings into research, business, and communities.
Objective
Data Scientist was labeled by Harvard Business Review as the sexiest job of the 21st century (http://www.hbs.edu/faculty/Pages/item.aspx?num=43110) and has been chosen as the best job in America, three years in a row according to Glassdoor. In such a new Age of Big Data and ever-evolving environment; managers, executives, researchers, teachers, and professionals of the discipline need access to the most current information about the concepts, issues, trends and technologies in a brand-new interdisciplinary area. The Encyclopedia of Data Science and Machine Learning will provide a collection of short chapters (3,000-5,000 words each), authored by leading experts, offering an in-depth description of concepts, issues, challenges, innovations, and opportunities in the field of Big Data and Machine Learning and their impact on all aspects of modern organizations and society in general.
Target Audience
This comprehensive volume is a critical resource for Big Data and Machine Learning practitioners and scientists, including industry professionals, technical managers, and corporate executives. In addition, educators, scholars, graduate students, and government officers will also find this book to be useful. Among the perspectives examined include historical underpinnings, strategic planning and policy, hot job prospects, and future directions, all of which are focused on the unique benefits and capabilities found in Industry 4.0.
Recommended Topics
https://www.igi-global.com/publish/call-for-papers/call-details/5266
Submission Procedure
Researchers and practitioners are invited to submit on or before June 18, 2021, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter via Propose Chapter > at the bottom of https://www.igi-global.com/publish/call-for-papers/call-details/5266. Authors will be notified by July 17, 2021 about the status of their proposals and sent chapter guidelines. Full chapters are expected to be submitted by September 16, 2021, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ <https://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, Encyclopedia of Data Science and Machine Learning. All manuscripts are accepted based on a double-blind peer review editorial process.
All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher
This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com<https://www.igi-global.com/>. This publication is anticipated to be released in 2022.

Important Dates
June 18, 2021:           Proposal Submission Deadline
July 17, 2021:            Notification of Acceptance
Sept. 16, 2021:           Full Chapter Submission
Dec. 6, 2021:              Review Results Returned
Feb. 14, 2022:            Final Acceptance Notification
Feb. 28, 2022:            Final Chapter Submission

Inquiries
For inquiries, please contact the editor: prof.johnwang at gmail.com<mailto:prof.johnwang at gmail.com>
John Wang, Professor
Montclair State University, USA