Big Data Recommender Systems - Volume 2 : Application Paradigms /

The increase in the volumes of data creates new challenges that require novel and more efficient solutions to handle big data and scalability issues. Today we are witnessing advances in many areas that are dependent on recommender systems such as social networks, e-commerce websites, search engines,...

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Bibliographic Details
Corporate Author: Institution of Engineering and Technology
Other Authors: Khalid, Osman (Editor), Khan, Samee U. (Editor), Zomaya, Albert Y. (Editor)
Format: eBook
Language:English
Published: Stevenage : IET, 2019.
Series:Computing.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:The increase in the volumes of data creates new challenges that require novel and more efficient solutions to handle big data and scalability issues. Today we are witnessing advances in many areas that are dependent on recommender systems such as social networks, e-commerce websites, search engines, blogs, and sensor networks. Many of these advances are due to the many developments in algorithmics and analytics, wireless networking, Internet of things, high performance computing, and more. Volume 2, Big Data Recommender Systems: Application Paradigms, presents a good overview of the many applications that show the richness of this field and its great potential.
Physical Description:1 online resource (536 pages)
ISBN:9781785619786
DOI:10.1049/PBPC035G