front cover of Big Data Recommender Systems
Big Data Recommender Systems
Algorithms, Architectures, Big Data, Security and Trust, Volume 1
Osman Khalid
The Institution of Engineering and Technology, 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.
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front cover of Big Data Recommender Systems
Big Data Recommender Systems
Application Paradigms, Volume 2
Osman Khalid
The Institution of Engineering and Technology, 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.
[more]

logo for The Institution of Engineering and Technology
Big Data Recommender Systems
Recent trends and advances
Osman Khalid
The Institution of Engineering and Technology, 2019
This timely volume combines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts and methodologies for complex applications. It includes original scientific contributions in the form of theoretical foundations, comparative analysis, surveys, case studies, techniques and tools. The authors give special attention to key topics such as data filtering and cleaning techniques for recommendations, novelty and diversity, privacy issues, security threats and their mitigation, trust, cold start, sparsity, scalability, application domains, and recommender system evaluations.
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