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

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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 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.

Inspec keywords: trusted computing; security of data; recommender systems; Big Data

Other keywords: trust measures; big data recommender systems; recommendation approaches; architectures; algorithms; security measures

Subjects: Search engines; Data handling techniques; Information networks; General and management topics

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