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Recommender Systems de Monideepa Roy

Recommender Systems: Intelligent Systems

Editat de Monideepa Roy, Pushpendu Kar, Sujoy Datta
en Limba Engleză Paperback – 19 dec 2024
This book presents a multi-disciplinary approach for development of Recommender Systems. It explains different types of pertinent algorithms with their comparative analysis, and their role for different applications including case studies. It explains Big Data behind Recommender System, making good decision support systems, etc.
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Specificații

ISBN-13: 9781032333229
ISBN-10: 1032333227
Pagini: 260
Dimensiuni: 233 x 156 x 18 mm
Greutate: 0.4 kg
Editura: Taylor & Francis Ltd.
Seria Intelligent Systems

Cuprins

1. Comparison of Different Machine Learning  Algorithms to Classify Whether or Not a Tweet Is about a Natural Disaster: A Simulation-Based Approach; 2. An End-to-End Comparison among Contemporary Content-Based Recommendation Methodologies; 3.  Neural Network-Based Collaborative Filtering for Recommender Systems; 4. Recommendation System and Big Data: Its Types and Applications; 5. The Role of Machine Learning /AI in Recommender Systems; 6. A Recommender System Based on TensorFlow Framework; 7. A Marketing Approach to Recommender Systems; 8. Applied Statistical Analysis in Recommendation Systems; 9.  An IoT-Enabled Innovative Smart Parking Recommender Approach; 10. Classification of Road Segments in Intelligent Traffic Management System; 11. Facial Gestures-Based Recommender System for Evaluating Online Classes; 12. Application of Swarm Intelligence in Recommender Systems; 13. Application of Machine-Learning Techniques in the Development of Neighbourhood-Based Robust Recommender Systems; 14. Recommendation Systems for Choosing Online Learning Resources: A Hands-On Approach

Notă biografică

Pushpendu Kar is an Assistant Professor in the School of Computer Science at the University of Nottingham Ningbo, China (China campus of the University of Nottingham UK). Before this, he was a Research Fellow in the Department of ICT and Natural Sciences at the Norwegian University of Science and Technology (NTNU), Norway; the Department of Electrical & Computer Engineering at the National University of Singapore (NUS); and the Energy Research Institute at Nanyang Technological University (NTU), Singapore. Dr. Kar completed his Ph.D., Master of Engineering, and Bachelor of Technology in Computer Science and Engineering from IIT Kharagpur, Jadavpur University, and University of Kalyani, respectively. Dr. Kar is an IEEE Senior Member. He received four research grants, three of them as Principal Investigator for conducting research-based projects. Dr. Kar has more than 12 years of teaching and research experience as well as one and a half years of industrial experience at IBM. Dr. Kar hasover 53 scholarly research papers and 05 patents published to his credit. His research areas are wireless sensor networks, IoT, content-centric networking, machine learning, and blockchain. 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.

Textul de pe ultima copertă

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.

Caracteristici

Studies different types of algorithms for recommender systems along with their comparative analysis Presents case studies of the application of recommender system in healthcare monitoring and military surveillance Shows how to design attack-resistant and trust-centric recommender systems for applications dealing with sensitive data