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The book includes a thorough examination of the many types of algorithms for recommender systems, as well as a comparative analysis of them. It addresses the problem of dealing with the large amounts of data generated by the recommender system. The book also includes two case studies on recommender system applications in healthcare monitoring and military surveillance. It demonstrates how to create attack-resistant and trust-centric recommender systems for sensitive data applications. This book provides a solid foundation for designing recommender systems for use in healthcare and defense.
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Monideepa Roy earned her Bachelor and Master degrees in Mathematics from IIT Kharagpur and her Ph.D. in CSE from Jadavpur University. Currently, she is Associate Professor at KIIT Deemed University, Bhubaneswar. Her areas of interest include remote health care, mobile computing, cognitive WSNs, remote sensing, recommender systems, sparse approximations, and artificial neural networks. At present, she has seven research scholars working with her in the above areas, and two more have successfully defended their theses under her guidance. She has several publications in reputed conferences and journals. She also has several book chapter publications and has also edited a book.
Sujoy Datta completed his M.Tech. from IIT Kharagpur. Currently, he is an Assistant Professor in theSchool of Computer Engineering at KIIT Deemed University. His research areas are wireless networks, computer security, elliptic curve cryptography and neural networks, remote health care, and recommender systems. He has published several papers in conferences and journals of international repute. He also has several book chapter publications and has also edited a book.
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