Recommender Systems: A Multi-Disciplinary Approach

English | 2023 | ISBN: 978-1032333212 | 280 Pages | PDF | 10 MB

Recommender Systems: A Multi-Disciplinary Approach 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. It explains Big Data behind Recommender System, marketing benefits, making good decision support systems, role of machine learning and artificial networks, and 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:

• 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, graduate students in computer science, electronics and communication engineering, mathematical science, and data science.