Description
Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data.
Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.
Author's/Editor's Biography
Anandakumar Haldorai (Ed.)
Dr.
Anandakumar Haldorai
serves as a Professor in CSE and Associate Dean – Research at Sri Eshwar College of Engineering. He has 18 years of experience in Engineering Education. He has received his Master’s in Software engineering from PSG College of Technology, Coimbatore and PhD in Information and Communication Engineering from PSG College of Technology. His research areas include Big Data, Cognitive Radio Networks,Mobile Communications and Networking Protocols. He has authored more than 172 research papers in reputed International Journals and IEEE conferences. He has authored 14 books and many book chapters with reputed publishers such as Springer and IGI. He is a passionate researcher and also Editor in Chief Keai – Elsevier – IJIN, Associate Editor IEEE Access, Area Editor – EAI Energy Web and served as a reviewer for IEEE, IET, Springer, Inderscience and Elsevier journals. He is also the guest editor of many journals with Elsevier, Springer, Inderscience, etc. He had been the General Chair, Session Chair, and Panelist in several conferences. He is a senior member of IEEE, IET, ACM and Fellow member of EAI research group.
Arulmurugan Ramu (Ed.)
Arulmurugan Ramu Received his PhD. degrees in Information and Communication Engineering from Anna University, Chennai, Tamil Nadu, India. He is currently working as Assistant Professor in the Department of Computer Science and Engineering, Presidency University, India. He received Young Faculty Award for 2018. He published many paper in Scopus indexed and SCI journals with Google scholar 61 citations.His research interests include Digital Image Processing, Biomedical Image Processing Computer vision, pattern recognition, and machine learning.