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2020 | OriginalPaper | Buchkapitel

Development and Analysis of Intelligent Recommendation System Using Machine Learning Approach

verfasst von : Pavlo Piletskiy, Dmytro Chumachenko, Ievgen Meniailov

Erschienen in: Integrated Computer Technologies in Mechanical Engineering

Verlag: Springer International Publishing

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Abstract

Recommendation systems have changed the way inanimate websites interact with their users. Instead of providing static information when users search and possibly buy products, recommendation systems increase the degree of interactivity to expand the possibilities provided to the user. Recommendation systems generate recommendations independently for each specific user based on his past purchases and searches, as well as on the basis of the behavior of other users. This article describes recommender systems and their algorithms. Recommendation system is developed using SVD algorithm. The architectural pattern MVC was used. The implementation represents a three-tier architecture (DAL, BLL, WEB). Program realization of recommendation system was made using .Net language.

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Vorheriges Kapitel Application of Artificial Neural Networks in the Problems of the Patient’s Condition Diagnosis in Medical Monitoring Systems

Nächstes Kapitel Non-linear Estimation Methods in Multi-objective Problems of Robust Optimal Design and Diagnostics of Systems Under Uncertainties

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Titel: Development and Analysis of Intelligent Recommendation System Using Machine Learning Approach
verfasst von: Pavlo Piletskiy
Dmytro Chumachenko
Ievgen Meniailov
Verlag: Springer International Publishing
Buch: Integrated Computer Technologies in Mechanical Engineering
Print ISBN: 978-3-030-37617-8

Electronic ISBN: 978-3-030-37618-5

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-37618-5_17

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