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Big Data Recommender Systems - Volume 2: Application Paradigms

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Editors: Osman Khalid 1 ; Samee U. Khan 2 ; Albert Y. Zomaya 3
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Publication Year: 2019

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.

Inspec keywords: Big Data; recommender systems

Other keywords: big data recommender systems; application paradigms

Subjects: Search engines; Database management systems (DBMS); Data handling techniques; General and management topics; Information networks

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