This book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book is a collection of high-quality peer-reviewed research papers presented in the Sixth International Conference on Computational Intelligence in Data Mining (ICCIDM 2021) held at Aditya Institute of Technology and Management, Tekkali, Andhra Pradesh, India, during December 11-12, 2021. The book addresses the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

Autorentext

Dr. Janmenjoy Nayak is working as Associate Professor, Aditya Institute of Technology and Management (AITAM),(An Autonomous Institution) Tekkali, AP, India. Being two times Gold Medalist in Computer Science in his career, he has been awarded with INSPIRE Research Fellowship from DST, Govt. of India (both as JRF and SRF level) and Best Researcher Award from Jawaharlal Nehru University of Technology, Kakinada, AP, for the AY: 2018-19 and many other awards from national and international academic agencies. He has edited 14 books and 8 special issues on the applications of computational intelligence, soft computing, and pattern recognition, published by reputed International publications. He has published more than 140 referred articles in various chapters, conferences, and international reputed peer-reviewed journals of Elsevier, Inderscience, Springer, IEEE, etc. He is Senior Member of IEEE and Life Member of some of the reputed societies like CSI India, IAENG (Hong Kong), etc. He has successfully conducted and is being associated with 14 international reputed series conferences like ICCIDM, HIS, ARIAM, CIPR, SCDA, etc. His area of interest includes data mining, nature-inspired algorithms, and applied artificial intelligence.

Dr. Himansu Sekhar Behera is working as Associate Professor in the Department of Information Technology, Veer Surendra Sai University of Technology (VSSUT), Burla, Odisha, India. He has received M.Tech. in Computer Science & Engineering from National Institute of Technology (N.I.T), Rourkela ,Odisha, India, and Doctor of Philosophy in Engineering (Ph.D.) from Biju Pattnaik University of Technology (BPUT), Rourkela, Govt. of Odisha, India, respectively. His research and development experience includes over 19 years in academia spanning different technical institutes in India. His research interest includes data mining, soft computing, evolutionary computation, machine intelligence, and distributed system. He has authored/co-authored over 150+ journal/conferences papers and chapters. He has edited 11 books and serves as Associate Editor /Member of the editorial/reviewer board of various international journals and also guest edited 08 special issues on various topics of Inderscience and IGI Global Journals. He has produced eight Ph.D.s in the area of data mining and time series forecasting using soft computing techniques.

Dr. Bighnaraj Naik is Assistant Professor in the Department of Computer Applications, Veer Surendra Sai University of Technology, Burla, Odisha, India. He received his doctoral degree from the Department of Computer Sc. Engineering & Information Technology, Veer Surendra Sai University of Technology, Burla, Odisha, India, Master's degree from SOA University, Bhubaneswar, Odisha, India, and Bachelor's degree from National Institute of Science and Technology, Berhampur, Odisha, India. He has published more than 120 research papers in various reputed peer-reviewed international conferences, referred journals and chapters. He has more than five years of teaching experience in the field of computer science and information technology. His area of interest includes data mining, soft computing, etc.

Dr. S. Vimal is working in the Department of Computer Science and Engineering, Ramco Institute of Technology, Tamil Nadu, India. He has around fourteen years of teaching experience, EMC certi ed Data Science Associate and CCNA certi ed professional too. He holds a Ph.D. in Information and Communication Engineering from Anna University, Chennai, and he received Master's degree from Anna University, Coimbatore. He organized various funded workshops and seminars. He has wide publications in the highly impact journals in the area of data analytics, networking, and security issues and published 04 chapters. He has hosted two special sessions for IEEE sponsored conference in Osaka, Japan, and Thailand. His areas of interest include game modeling, arti cial intelligence, machine learning, and big data analytics. He is Senior Member in IEEE, ACM, and ISTE. He has hosted 21 special issues in IEEE, Elsevier, and Springer journals. He has served as Guest Editor for SCI journals and edited 3 books in reputed International publishers. Dr. Danilo Pelusi has received the Ph.D. degree in Computational Astrophysics from the University of Teramo, Italy. Presently, he is holding the position of Associate Professor at the Faculty of Communication Sciences, University of Teramo. Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Access, International Journal of Machine Learning and Cybernetics (Springer) and Array (Elsevier), he served as Guest Editor for Elsevier, Springer and Inderscience journals, as Program Member of many conferences and as Editorial Board Nember of many journals. Reviewer of reputed journals such as IEEE Transactions on Fuzzy Systems and IEEE Transactions on Neural Networks and Machine Learning, his research interests include intelligent computing, communication system, fuzzy logic, neural networks, information theory, and evolutionary algorithms.

Inhalt

Multi-sensor data fusion for Occupancy detection using Dempster-Shafer Theory.- Sentiment Analysis: A Recent Survey with Applications and a Proposed Ensemble Algorithm.- An Automated System for Facial Mask Detection and Social Distancing During Covid - 19 Pandemic.- Detection of Insider Threats Using Deep Learning: A Review.- An Incisive analysis of Advanced Persistent Threat detection using Machine learning Techniques.- Intelligent Computing Systems For Diagnosing Plant Diseases.- Multimodal MRI Analysis for Segmentation of Intra-tumoral Regions of High-Grade Glioma using VNet and WNet based deep models.- Early Onset Alzheimer Disease Classification using Convolution Neural Network.