Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis.
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Table of Contents
1. An Introduction to Data Mining in Social Networks 2. Performance Tuning of Android Applications using Clustering and Optimization Heuristics 3. Sentiment analysis of Social Media data evolved from COVID-19 cases Maharashtra 4. COVID-19 Outbreak Analysis and Prediction Using Statisical Learning 5. Verbal Sentiment Analysis and Detection using Recurrent Neural Network 6. A Machine Learning approach to aid Paralysis patients using EMG signals 7. Influence of Travelling on Social Behaviour 8. A Study on Behaviour Analysis in Social Network 9. Recent Trends in Recommendation System using Sentiment Analysis 10. Data Visualization: Existing Tools and Techniques 11. An intelligent agent of Mining of Frequent Patterns on Uncertain Graphs 12. Mining Challenges in Large Scale IoT Data Framework A Machine Learning Perspective 13. Conclusion
Authors
Sourav De Associate Professor of Computer Science and Engineering, Cooch Behar Government Engineering College, Cooch Behar, West Bengal, India. Dr. Sourav De completed his PhD in Computer Science and Technology at the Indian Institute of Engineering & Technology, Shibpur, Howrah, India in 2015. He is currently an Associate Professor of Computer Science & Engineering at Cooch Behar Government Engineering College, West Bengal. He is a co-author of one book, the co-editor of twelve books, and has more than 54 research publications in internationally reputed journals, international edited books, international IEEE conference proceedings, and one patent to his credit. His research interests include soft computing, pattern recognition, image processing, and data mining. Dr. De is a senior member of IEEE and a member of ACM, Institute of Engineers (IEI), Computer Science Teachers Association (CSTA), Institute of Engineers and IAENG, Hong Kong. He is a life member of ISTE, India. Sandip Dey Associate Professor, Department of Computer Science, Sukanta Mahavidyalaya, Jalpaiguri, Dhupguri, West Bengal, India. Dr. Sandip Dey completed his PhD in Computer Science and Engineering at Jadavpur University, India in 2016. He is currently an Assistant Professor in the Department of Computer Science at Sukanta Mahavidyalaya, Jalpaiguri. He has more than 40 research publications in international journals, book chapters and conference proceedings to his credit. He has authored or edited four books, published by John Wiley & Sons and Elsevier. His research interests include soft computing, quantum computing and image analysis. Siddhartha Bhattacharyya VSB Technical University of Ostrava, Czech Republic. Siddhartha Bhattacharyya is a Senior Researcher in the Faculty of Electrical Engineering and Computer Science of VSB Technical University of Ostrava, Czech Republic. He is also serving as the Scientific Advisor of Algebra University College, Zagreb, Croatia. Prior to this, he served as the Principal of Rajnagar Mahavidyalaya, Rajnagar, Birbhum. He was a professor at CHRIST (Deemed to be University), Bangalore, India, and also served as the Principal of RCC Institute of Information Technology, Kolkata, India. He is the recipient of several coveted national and international awards. He received the Honorary Doctorate Award (D. Litt.) from the University of South America and the SEARCC International Digital Award ICT Educator of the Year in 2017. He was appointed as the ACM Distinguished Speaker for the tenure 2018-2020. He has been appointed as the IEEE Computer Society Distinguished Visitor for the tenure 2021-2023. He has co-authored six books, co-edited 75 books, and has more than 300 research publications in international journals and conference proceedings to his credit. Surbhi Bhatia Khan Assistant Professor, Department of Data Science, School of Science, Engineering and Environment, University of Salford, Manchester, United Kingdom. Surbhi Bhatia Khan is Doctorate in Computer Science and Engineering in the area of MachineLearning and Social Media Analytics. She earned Project Management Professional Certification
from reputed Project Management Institute, USA. She is currently working in the Department of
Data Science, School of Science, Engineering and Environment, University of Salford, Manchester,
United Kingdom. She has more than 11 years of academic and teaching experience in different universities. She is the awardee of the Research Excellence award given by King Faisal University, Saudi Arabia, in 2021. She has published 100� papers in many reputed journals in high indexed outlets. She has around 12 international patents from India, Australia, and the United States. She has successfully authored 3 books and has also edited 12 books. She has completed many projects approved from Ministry of Education, Saudi Arabia, and Deanship of Scientific Research in different universities in Saudi Arabia and from India. Her area of interest is Knowledge Management, Information Systems, Machine Learning, and Data Science.
