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.
Key Features
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
Readership
Master Degree/Ph.D. students, professionals and researchers in Computer Science working in data science, big data, and machine learning
Table of Contents
A. Foundations and Architectural Models of Cognitive Big Data and Meta heuristics 1. Cognitive Computing fundamentals like perception, memory, reasoning, emotion, and problem solving 2. Cognitive Computing techniques using artificial intelligence, pattern and speech recognition, and natural language processing 3. Cognitive approaches within data mining and machine learning techniques 4. Big Data Infrastructure for Cognition and Distributed Data Centers for Cognition 5. Meta heuristics in classification, clustering and frequent pattern mining problems 6. Nature-inspired computing and Optimization algorithms 7. Meta heuristics and swarm intelligence approach 8. Use of Computational intelligence and Intelligent computing approaches in engineering domains 9. Big Data, Clouds and Internet of Things (IoT) 10. Dimensionality reduction models with Meta heuristics 11. Neuro-evolutionary and fuzzy models in big data and cognitive analytics 12. Innovative methods for cognitive business big data analytics 13. Cognitive techniques for mining unstructured, spatial-temporal, streaming and multimedia data 14. Data-driven large scale optimization architectures 15. Ensemble learning with Meta heuristics optimization
B. Application Domains and use of Cognitive Big data with Meta heuristics 16. Applications in Logistics, Transportation and Supply Chain Management 17. Cognitive Sensor-Networks applications 18. Algorithm development for big data analysis in E-health and Telemedicine 19. Biomedical Image Processing and Big Data Applications 20. Data Applications of Cognitive Communication 21. Intelligent distributed applications in e-commerce 22. Applications in Economics and Finance 23. Applications in Aeronautics 24. Applications in financial analysis 25. Applications in Cyber security and Intelligence 26. Applications in Traffic Optimization 27. Applications in routing of energy efficient communication networks 28. Other Miscellaneous applications
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.
Affiliations and Expertise
Assistant Professor, School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India
Hrudaya Tripathy
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.
Affiliations and Expertise
Associate Professor, School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India
Pradeep Mallick
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
Affiliations and Expertise
Senior Associate Professor, School of Computer Engineering, Kalinga Institute of Industrial technology (KIIT) Deemed to be University, Odisha, India
Arun Sangaiah
Dr. Arun Kumar Sangaiah received his Master of Engineering from Anna University and Ph.D. from VIT University, India. He is currently as 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. Moreover, he has holding visiting professor positions in China, France, Japan, South Korea. Further, he has been visited many research centers and universities in China, Japan, France, Singapore and South Korea for join collaboration towards research projects and publications. Dr. Sangaiah’s outstanding scientific production spans over 200+ contributions published in high standard ISI journals, such as IEEE-TII, IEEE-Communication Magazine, IEEE Systems and IEEE IoT. In addition, he has authored/edited 8 books (Elsevier, Springer and others) and edited 50 special issues in reputed ISI journals, such as IEEE-Communication Magazine, IEEE-TII, IEEE-IoT, ACM transaction on Intelligent Systems and Technology etc. He has also registered one Indian patent in the area of Computational Intelligence. His Google Scholar Citations reached 5000+ with h-index: 40+ and i10-index: 150+. Further, Dr. Sangaiah is responsible for EiC, Editorial Board Member and Associate Editor of many reputed ISI journals.Finally, he has received many awards that includes,Chinese Academy of Sciences-PIFI overseas visiting scientist award, UPEC-France Visiting Scholar award, Carrers-360 Top-10 Outstanding Researchers award and etc.
Affiliations and Expertise
School of Computer Science, The University of Adelaide, Australia
Gyoo-Soo Chae
Professor Gyoo-Soo Chae works in the Division of ICT at Baekseok University, Cheonan in South Korea.
Affiliations and Expertise
Professor, Division of ICT, Baekseok University, Cheonan, South Korea
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