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Development and Analysis of Intelligent Recommendation System Using Machine Learning Approach

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Integrated Computer Technologies in Mechanical Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1113))

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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Author information

Authors and Affiliations

  1. National Aerospace University “Kharkiv Aviation Institute”, Chkalova Street 17, Kharkiv, 61070, Ukraine

    Pavlo Piletskiy, Dmytro Chumachenko & Ievgen Meniailov

Authors
  1. Pavlo Piletskiy
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  2. Dmytro Chumachenko
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  3. Ievgen Meniailov
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Corresponding author

Correspondence to Dmytro Chumachenko .

Editor information

Editors and Affiliations

  1. National Aerospace University "Kharkiv Aviation Institute", Kharkov, Ukraine

    Mykola Nechyporuk

  2. National Aerospace University "Kharkiv Aviation Institute", Kharkov, Ukraine

    Vladimir Pavlikov

  3. National Aerospace University "Kharkiv Aviation Institute", Kharkov, Ukraine

    Dmitriy Kritskiy

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Piletskiy, P., Chumachenko, D., Meniailov, I. (2020). Development and Analysis of Intelligent Recommendation System Using Machine Learning Approach. In: Nechyporuk, M., Pavlikov, V., Kritskiy, D. (eds) Integrated Computer Technologies in Mechanical Engineering. Advances in Intelligent Systems and Computing, vol 1113. Springer, Cham. https://doi.org/10.1007/978-3-030-37618-5_17

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  • DOI: https://doi.org/10.1007/978-3-030-37618-5_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37617-8

  • Online ISBN: 978-3-030-37618-5

  • eBook Packages: EngineeringEngineering (R0)

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