Recommender Systems: Algorithms and their Applications [electronic resource] / by Pushpendu Kar, Monideepa Roy, Sujoy Datta.

Por: Kar, Pushpendu [author.]Colaborador(es): Roy, Monideepa [author.] | Datta, Sujoy [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Transactions on Computer Systems and NetworksEditor: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XIV, 165 p. 64 illus., 43 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789819705382Tema(s): Database management | Artificial intelligence | Quantitative research | Database Management System | Artificial Intelligence | Data Analysis and Big DataFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 005.7 Clasificación LoC:QA76.9.D3Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Overview of Recommendtion system Algorithms -- Collaborative Filtering -- Matrix decomposition for Recommendtion -- Clustering.
En: Springer Nature eBookResumen: 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.
Star ratings
    Valoración media: 0.0 (0 votos)
Existencias
Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos 1 No para préstamo

Introduction -- Overview of Recommendtion system Algorithms -- Collaborative Filtering -- Matrix decomposition for Recommendtion -- Clustering.

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.

UABC ; Perpetuidad

Con tecnología Koha