Cognitive Big Data Intelligence with a Metaheuristic Approach (Cognitive Data Science in Sustainable Computing) - Softcover

Softcover

ISBN 10: 0323851177 ISBN 13: 9780323851176

Publisher: Academic Press, 2021

Synopsis

Cognitive Big Data Intelligence with a Metaheuristic Approach presents an exact and compact organization of content relating to the latest metaheuristics methodologies based on new challenging big data application domains and cognitive computing. The combined model of cognitive big data intelligence with metaheuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. Various real-time case studies and implemented works are discussed in this book for better understanding and additional clarity.

This book presents an essential platform for the use of cognitive technology in the field of Data Science. It covers metaheuristic methodologies that can be successful in a wide variety of problem settings in big data frameworks.

• Provides a unique opportunity to present the work on the state-of-the-art of metaheuristics approach in the area of big data processing developing automated and intelligent models
• Explains different, feasible applications and case studies where cognitive computing can be successfully implemented in big data analytics using metaheuristics algorithms
• Provides a snapshot of the latest advances in the contribution of metaheuristics frameworks in cognitive big data applications to solve optimization problems

About this title

About the Authors

Dr. Sushruta Mishra is working as an Assistant Professor in the School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. He pursued his M.Tech from IIIT, Bhubaneswar in 2012 and has completed his Ph.D in Computer Science from KIIT University, Bhubaneswar, Odisha, India in 2017. Dr. Mishra has more than 7 years of teaching experience in various educational institutions. He has handled many subjects such as Computer networks, Data mining, Software engineering, Machine learning etc during his academic experience. His research interest includes Image processing, Machine Learning, Internet of Things and Cognitive computing. He has published several research articles in reputed scopus indexed International Journals, Edited books and Conferences.

Dr. Hrudaya Kumar Tripathy is presently working as Associate Professor in School of Computer Engineering at KIIT University, Bhubaneswar, Odisha, India and Program Head of M.Tech(CSE) courses. He has received M.Tech degree in CSE from IIT Guwahati in 2006, and obtained Ph.D degree in Computer Science from Berhampur University, Berhampur, Odisha, India in Computer Science in 2010. Dr. Tripathy had been a visiting faculty in Asia Pacific University, Kuala Lumpur, Malaysia and University Utara Malaysia, Sintok, Malaysia. He is having 20 years of teaching experience with Post Doctorate from Malaysia. He has handled various subjects like Software engineering, Machine learning, Business intelligence etc. His research interest includes Neural Networks, Pattern Recognition, Software Engineering, Machine learning and Big Data. He has published several research papers in various journals and conferences. Besides, academic experience he had been actively involved in various administrative responsibilities in his previous job positions. Dr. Tripathy is a senior member of IEEE, life member of CSI & having membership in other different professional bodies such as IET, IACSIT, IAENG.Dr. Hrudaya Kumar Tripathy is presently working as Associate Professor in School of Computer Engineering at KIIT University, Bhubaneswar, Odisha, India and Program Head of M.Tech(CSE) courses. He has received M.Tech degree in CSE from IIT Guwahati in 2006, and obtained Ph.D degree in Computer Science from Berhampur University, Berhampur, Odisha, India in Computer Science in 2010. Dr. Tripathy had been a visiting faculty in Asia Pacific University, Kuala Lumpur, Malaysia and University Utara Malaysia, Sintok, Malaysia. He is having 20 years of teaching experience with Post Doctorate from Malaysia. He has handled various subjects like Software engineering, Machine learning, Business intelligence etc. His research interest includes Neural Networks, Pattern Recognition, Software Engineering, Machine learning and Big Data. He has published several research papers in various journals and conferences. Besides, academic experience he had been actively involved in various administrative responsibilities in his previous job positions. Dr. Tripathy is a senior member of IEEE, life member of CSI & having membership in other different professional bodies such as IET, IACSIT, IAENG.

Dr. Pradeep Kumar Mallick is currently working as Senior Associate Professor in the School of Computer Engineering , Kalinga Institute of Industrial technology (KIIT) Deemed to be University, Odisha, India .He has also served as Professor and Head Department of Computer Science and Engineering , Vignana Bharathi Institute of Technology, Hyderabad . He has completed his Post Doctoral Fellow (PDF) in Kongju National University South Korea , PhD from Siksha Ó’ Anusandhan University, M. Tech. (CSE) from Biju Patnaik University of Technology (BPUT), and MCA from Fakir Mohan University Balasore, India. Besides academics, he is also involved various administrative activities, Member of Board of Studies, Member of Doctoral Research Evaluation Committee, Admission Committee etc. His area of research includes Algorithm Design and Analysis, and Data Mining, Image Processing, Soft Computing, and Machine Learning. Now he is the editorial member of Korean Convergence Society for SMB .He has published 9 books and more than 70 research papers in National and international journals and conference proceedings in his credit

Prof. Arun Kumar Sangaiah received his PhD from the School of Computer Science and Engineering, VIT University, Vellore, India. He is currently a Full Professor with National Yunlin University of Science and Technology, Taiwan. He is also a Professor at the School of Computing Science and Engineering, VIT University, Vellore, India. His areas of research interest include machine learning, Internet of Things, Sustainable Computing. He has published more than 300 research articles in refereed journals, 11 edited books, one patent (held and filed), as well as four projects funded by MOST-TAIWAN, one funded by Ministry of IT of India, and several international projects (CAS, Guangdong Research fund, Australian Research Council). Dr. Sangaiah has received many awards, Yushan Young Scholar, Clarivate Top 1% Highly Cited Researcher (2021,2022, 2023), Top 2% Scientist (Standord Report-2020,2021,2022, 2023), PIFI-CAS fellowship, Top-10 outstanding researcher, CSI significant Contributor etc. He is also serving as Editor-in-Chief and/or Associate Editor of various reputed ISI journals. Dr. Sangaiah is a visiting scientist (2018-2019) with Chinese Academy of Sciences (CAS), China and visiting researcher of Université Paris-Est (UPEC), France (2019-2020) and etc.

Professor Gyoo-Soo Chae works in the Division of ICT at Baekseok University, Cheonan in South Korea.

From the Back Cover

Cognitive Big Data Intelligence with Meta-Heuristic Approach presents an exact and compact organization of contents related to the latest meta-heuristics methodologies based on new challenging big data application domains and cognitive computing with proper explanation wherever required.

The combined model of cognitive big data intelligence with meta-heuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. It can be further used to enhance customer interactions with the help of robotic process automation. It presents other technical aspects and alternatives to traditional tools, algorithms, and methodologies. Various real-time case studies and implemented works will be discussed in this book for better understanding and more clarity to readers.

This book presents an essential platform for the use of cognitive technology in the field of Data Science. It covers meta-heuristic methodologies that can be successful in a wide variety of problem settings in big data frameworks.

Edition details

• Publisher: Academic Press
• Publication date: 2021
• ISBN 10: 0323851177
• ISBN 13: 9780323851176
• Binding: Paperback
• Language: English
• Edition number: 1
• Number of pages: 372
• Editor: Mishra Sushruta, Tripathy Hrudaya Kumar, Mallick Pradeep Kumar, Sangaiah Arun Kumar, Chae Gyoo-Soo