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This book presents a compilation of current trends, technologies, and challenges in connection with Big Data. Many fields of science and engineering are data-driven, or generate huge amounts of data that are ripe for the picking. There are now more sources of data than ever before, and more means of capturing data. At the same time, the sheer volume and complexity of the data have sparked new developments, where many Big Data problems require new solutions. Given its scope, the book offers a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of Big Data applications.
List of contents
A review of Recommender System and related Dimensions.- Collaborative Filtering Techniques in Recommendation Systems.- Predicting Users' Interest through ELM basedCollaborative Filtering.- Application of Community Detection Technique in Text Mining.- Sentiment Analysis on WhatsApp Group Chat using R.- A Recent Survey on Information Hiding Techniques.- Investigation of Feature Selection Techniques on Performance of Automatic Text Categorization.- Identification and Analysis of Future User Interactions Using Some Link Prediction Methods in Social Networks.- Sentiment Prediction of Facebook Status updates of youngsters.- Logistic Regression for the Diagnosis of Cervical Cancer.- Automatic Examination Timetable Scheduling Using Particle Swarm Optimization and Local Search Algorithm.- Personality Trait Identification for Written Texts Using MLNB.- Deep neural network compression via knowledge distillation for embedded vision applications.
About the author
Dr Rajesh K Shukla is a Professor and Head of the Department of Computer Science and Engineering, SIRT, Bhopal, India. With more than 20 years of teaching and research experience he has authored 8 books and has published/presented has more than 40 papers in international journals and conferences. Dr Shukla received an ISTE U.P. Government National Award in 2015 and various prestigious awards from the Computer Society of India. His research interests include recommendation systems and machine learning. He is fellow of IETE, a senior member of IEEE, a life member of ISTE, ISCA, and a member of ACM and IE(I).
Dr Jitendra Agrawal is a member of the faculty at the Department of Computer Science & Engineering, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India. His research interests include data mining and computational intelligence. He has authored 02 books and published more than 60 papers in international journals and conferences. Dr Agrawal is a senior member of IEEE, life member of CSI, ISTE and member of IAENG. He has served as part of the program committees for several international conferences organised in countries such as the USA, India, New Zealand, Korea, Indonesia and Thailand.
Dr Sanjeev Sharma is a Professor and Head of the School of Information Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, MP, India. He has over 29 years of teaching and research experience and received the World Education Congress Best Teacher Award in Information Technology. His research interests include mobile computing, ad-hoc networks, image processing and information security. He has edited proceedings of several national and international conferences and published more than 150 research papers in reputed journals. He is a member of IEEE, CSI, ISTE and IAENG.
Dr G S Tomer is the Director of THDC Institute of Hydropower Engineering and Technology (Government of Uttarakhand), Tehri, India. He received the International Plato award for Educational Achievements in 2009. He completed his doctorate in Electronics Engineering from RGPV Bhopal and postdoctorate from the University of Kent, United Kingdom.
Dr Tomar has more than 30 years of teaching and research experience and has published over 200 research papers in reputed journals, as well as 11 books and 7 book chapters. He is a senior member of IEEE, ACM and IACSIT, a fellow of IETE and IE(I), and a member of CSI and ISTE. He has also edited the proceedings of more than 20 IEEE conferences and has been the general chair of over 30 Conferences.
Summary
This book presents a compilation of current trends, technologies, and challenges in connection with Big Data. Many fields of science and engineering are data-driven, or generate huge amounts of data that are ripe for the picking. There are now more sources of data than ever before, and more means of capturing data. At the same time, the sheer volume and complexity of the data have sparked new developments, where many Big Data problems require new solutions.
Given its scope, the book offers a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of Big Data applications.
