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Recommender systemsalgorithms and their applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Recommender systemsby Pushpendu Kar, Monideepa Roy, Sujoy Datta.
Reminder of title:	algorithms and their applications /
Author:	Kar, Pushpendu.
other author:	Roy, Monideepa.
Published:	Singapore :Springer Nature Singapore :2024.
Description:	xiv, 165 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Recommender systems (Information filtering)
Online resource:	https://doi.org/10.1007/978-981-97-0538-2
ISBN:	9789819705382$q(electronic bk.)

Recommender systemsalgorithms and their applications /
Kar, Pushpendu.

Recommender systemsalgorithms and their applications /[electronic resource] :by Pushpendu Kar, Monideepa Roy, Sujoy Datta. - Singapore :Springer Nature Singapore :2024. - xiv, 165 p. :ill. (some col.), digital ;24 cm. - Transactions on computer systems and networks,2730-7492. - Transactions on computer systems and networks..

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.

ISBN: 9789819705382$q(electronic bk.)

Standard No.: 10.1007/978-981-97-0538-2doiSubjects--Topical Terms:

310886
Recommender systems (Information filtering)

LC Class. No.: ZA3084 / .K37 2024

Dewey Class. No.: 025.04

Recommender systemsalgorithms and their applications /
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505 0 $a Introduction -- Overview of Recommendtion system Algorithms -- Collaborative Filtering -- Matrix decomposition for Recommendtion -- Clustering.
520 $a 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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