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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.
