Big Data Recommender Systems: Volume 1 : Algorithms, Architectures, Big Data, Security and Trust

ISBN 10: 1785619756 / ISBN 13: 9781785619755

Published by The Institution of Engineering and Technology, 2019

Seller Inventory # 369570665

Synopsis:

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 1 contains 14 chapters addressing foundations, algorithms and architectures, approaches for big data, and trust and security measures. Volume 2 covers a broad range of application paradigms for recommender systems over 22 chapters.

About the Authors:

Osman Khalid is assistant professor at the department of computer sciences, COMSATS Institute of Information Technology, Abbottabad, Pakistan. His research interests include recommender systems, trust and reputation system, disaster response systems, delay tolerant networks, wireless networks, and fog computing.

Samee U. Khan is associate professor of electrical and computer engineering at the North Dakota State University, USA. His research interests include optimization, robustness, and security of systems.

Albert Y. Zomaya is chair professor of high performance computing & networking and Australian research council professorial fellow in the School of Information Technologies, The University of Sydney, Australia. He is also the director of the Centre for Distributed and High Performance Computing.

Bibliographic Details

Title: Big Data Recommender Systems: Volume 1 : ...
Publisher: The Institution of Engineering and Technology
Publication Date: 2019
Binding: Hardcover
Condition: New