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(Ebook) Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical, Agricultural and Other Industries by Sachi Nandan Mohanty (editor), Jyotir Moy Chatterjee (editor), Sarika Jain (editor), Ahmed A. Elngar (editor), Priya Gupta (editor) ISBN 9781119711575, 1119711576

  • SKU: EBN-11290510
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Instant download (eBook) Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical, Agricultural and Other Industries after payment.
Authors:Sachi Nandan Mohanty (editor), Jyotir Moy Chatterjee (editor), Sarika Jain (editor), Ahmed A. Elngar (editor), Priya Gupta (editor)
Pages:448 pages.
Year:2020
Editon:1
Publisher:Wiley-Scrivener
Language:english
File Size:10.31 MB
Format:pdf
ISBNS:9781119711575, 1119711576
Categories: Ebooks

Product desciption

(Ebook) Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical, Agricultural and Other Industries by Sachi Nandan Mohanty (editor), Jyotir Moy Chatterjee (editor), Sarika Jain (editor), Ahmed A. Elngar (editor), Priya Gupta (editor) ISBN 9781119711575, 1119711576

This book is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior.  It comprehensively covers the topic of recommender systems, which provide personalized recommendations of items or services to the new users based on their past behavior.  Recommender system methods have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising.

This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommendations in agricultural or healthcare domains and contexts, the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. This book illustrates how this technology can support the user in decision-making, planning and purchasing processes in agricultural & healthcare sectors.

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