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Recommender System Using K-Nearest Neighbors and Singular Value Decomposition Algorithms: A Hybrid Approach

  • Rounick PalitEmail author
  • Rajdeep ChatterjeeEmail author
Conference paper
  • 11 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1119)

Abstract

Recommender systems have found their importance in many parts of our life, from helping us decide what product to buy next to helping us discover songs of different genres. This article provides some basics of recommender systems and how to implement them using content and collaborative-based filtering methods. The model takes a matrix of user ratings for books as input and top recommendations are generated. It also discusses hybrid or mixed recommender systems and how they can provide better recommendations to users. It identifies areas that need enhancement for future implementation.

Keywords

Recommender system K-Nearest Neighbors Singular Value Decomposition Correlation 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.KIIT UniversityBhubaneswarIndia

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