Big Data Recommender Systems – Volume 2: Application Paradigms

Editors : Osman Khalid, Samee U. Khan Albert Y. Zomaya 

Publisher The Institution of Engineering & Technology (IET)
Publication Year 2019
eISBN 9781785619786
ISBN 9781785619779
Page 536
Language English

 

Description

First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users’ data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges. Divided into two volumes, this comprehensive set covers recent advances, challenges, novel solutions, and applications in big data recommender systems. Volume 2 covers a broad range of application paradigms for recommender systems over 22 chapters. Volume 1 contains 14 chapters addressing foundations, algorithms and architectures, approaches for big data, and trust and security measures.