Recommender Systems - Couverture rigide

Livre 2 sur 2: Intelligent Systems
 
9781032333212: Recommender Systems

Synopsis

Recommender Systems: A Multi-Disciplinary Approach presents a multi-disciplinary approach for the development of recommender systems. It explains different types of pertinent algorithms with their comparative analysis and their role for different applications. This book explains the big data behind recommender systems, the marketing benefits, how to make good decision support systems, the role of machine learning and artificial networks, and the statistical models with two case studies. It shows how to design attack resistant and trust-centric recommender systems for applications dealing with sensitive data.

Features of this book:

  • Identifies and describes recommender systems for practical uses
  • Describes how to design, train, and evaluate a recommendation algorithm
  • Explains migration from a recommendation model to a live system with users
  • Describes utilization of the data collected from a recommender system to understand the user preferences
  • Addresses the security aspects and ways to deal with possible attacks to build a robust system

This book is aimed at researchers and graduate students in computer science, electronics and communication engineering, mathematical science, and data science.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l?auteur

Monideepa Roy, Pushpendu Kar, Sujoy Datta

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Autres éditions populaires du même titre

9781032333229: Recommender Systems

Edition présentée

ISBN 10 :  1032333227 ISBN 13 :  9781032333229
Editeur : CRC Press, 2024
Couverture souple