Big Data Recommender Systems: Algorithms, Architectures, Big Data, Security and Trust

Big Data Recommender Systems: Algorithms, Architectures, Big Data, Security and Trust
ePUB
  • eBook:
    Big Data Recommender Systems: Algorithms, Architectures, Big Data, Security and Trust
  • Author:
    Osman Khalid, Samee U. Khan, Albert Y. Zomaya
  • Edition:
    1 edition
  • Categories:
  • Data:
    August 29, 2019
  • ISBN:
    1785619756
  • ISBN-13:
    9781785619755
  • Language:
    English
  • Pages:
    368 pages
  • Format:
    ePUB

Book Description
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.


Content

1. Introduction to big data recommender systems—volume 1
2. Theoretical foundations for recommender systems
3. Benchmarking big data recommendation algorithms using Hadoop or Apache Spark
4. Efficient and socio-aware recommendation approaches for bigdata networked systems
5. Novel hybrid approaches for big data recommendations
6. Deep generative models for recommender systems
7. Recommendation algorithms for unstructured big data such as text, audio, image and video
8. Deep segregation of plastic (DSP): segregation of plastic and nonplastic using deep learning
9. Spatiotemporal recommendation with big geo-social networking data
10. Recommender system for predicting malicious Android applications
11. Security threats and their mitigation in big data recommender systems
12. User's privacy in recommendation systems applying online social network dаta: a survey and taxonomy
13. Private entity resolution for big data on Apache Spark using multiple phonetic codes
14. Deep learning architecture for big data analytics in detecting intrusions and malicious URL

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