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Recommender System With Machine Learning And Artificial Intelligence Practical Tools And Applications In Medical Agricultural And Other Industries 1st Edition Sachi Nandan Mohanty Editor

  • SKU: BELL-11290510
Recommender System With Machine Learning And Artificial Intelligence Practical Tools And Applications In Medical Agricultural And Other Industries 1st Edition Sachi Nandan Mohanty Editor
$ 31.00 $ 45.00 (-31%)

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Recommender System With Machine Learning And Artificial Intelligence Practical Tools And Applications In Medical Agricultural And Other Industries 1st Edition Sachi Nandan Mohanty Editor instant download after payment.

Publisher: Wiley-Scrivener
File Extension: PDF
File size: 10.31 MB
Pages: 448
Author: Sachi Nandan Mohanty (editor), Jyotir Moy Chatterjee (editor), Sarika Jain (editor), Ahmed A. Elngar (editor), Priya Gupta (editor)
ISBN: 9781119711575, 1119711576
Language: English
Year: 2020
Edition: 1

Product desciption

Recommender System With Machine Learning And Artificial Intelligence Practical Tools And Applications In Medical Agricultural And Other Industries 1st Edition Sachi Nandan Mohanty Editor by Sachi Nandan Mohanty (editor), Jyotir Moy Chatterjee (editor), Sarika Jain (editor), Ahmed A. Elngar (editor), Priya Gupta (editor) 9781119711575, 1119711576 instant download after payment.

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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