Data Analytics for Social Microblogging Platforms (Hybrid Computational Intelligence for Pattern Analysis and Understanding) - Softcover

Dutta; Das; Ghosh; Samanta

Softcover

ISBN 10: 0323917852 ISBN 13: 9780323917858

Publisher: Academic Press, 2022

Synopsis

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data.

• Investigates various methodologies and algorithms for data summarization, clustering and classification
• Covers both theory and practical applications from around the world, across all related disciplines of Intelligent Information Filtering and Organization Systems
• Explores different challenges and issues related to spam filtering, attribute selection, and classification for large datasets

About this title

About the Authors

Soumi Dutta works in the Institute of Engineering and Management, Kolkata, West Bengal, India.

Asit Kumar Das is Professor of Computer Science and Technology, at the Indian Institute of Engineering Science and Technology Shibpur, Howrah. He is also the Head of the Center of Healthcare Science and Technology of the Institute. His area of research interest includes data mining and pattern recognition, social networks, bioinformatics, machine learning and soft computing, text, audio and video data analysis.

Dr. Ghosh is an Assistant Professor in the Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, India. His primary research interests are in social network analysis, legal data analytics, and algorithmic bias and fairness. His research uses techniques from machine learning, natural language processing, information retrieval, and complex network theory. He received his PhD in Computer Science from IIT Kharagpur in 2013. He is a Humboldt Post-doctoral research fellow at the Max Planck Institute for Software Systems (MPI-SWS), Germany. He has also been an Assistant Professor at the Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, India.

Debabrata Samanta is an Assistant Professor & Program Head, at the Department of Computing and Information Technologies, Rochester Institute of Technology, Kosovo, Europe. He obtained his Ph.D. in Computer Science and Engg. in the area of SAR Image Processing. He is keenly interested in Interdisciplinary Research and development and has experience spanning fields of SAR Image Analysis, Video surveillance, a Heuristic algorithm for Image Classification, Deep Learning Framework for Detection and Classification, Blockchain, Statistical Modelling, Wireless Adhoc Networks, Natural Language Processing. He has successfully completed six Consultancy Projects. He owns 22 Patents (4 Design Indian Patents and 2 Australian patents Granted, 16 Indian Patents published) and 2 copyrights. He has authored or co-authored over 224 research papers; he has co-authored 13 books and co-edited 13 books. He has presented various papers at international conferences and received Best Paper awards. He is an IEEE Senior Member, an Associate Life Member of the Computer Society of India (CSI), and a Life Member of the Indian Society for Technical Education (ISTE).

From the Back Cover

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets and the larger field which focuses on information, data, and knowledge, in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization, and classification. Chapters will focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data to address the most innovative developments, as well as research issues and solutions in massive data computations and their applications.

Edition details

• Publisher: Academic Press
• Publication date: 2022
• Language: English
• ISBN 10: 0323917852
• ISBN 13: 9780323917858
• Binding: Paperback
• Edition number: 1
• Number of pages: 328