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A Concurrent Recommender System Based on Social Network

  • Rachael Chertok
  • Nicholas Cockcroft
  • Sourav DuttaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10975)

Abstract

Recommender systems are widely used to improve sales for online retailers. Due to the large number of users and items, reducing computation time and space requirement for a recommender system has become challenging. In this paper, we propose a simple and effective recommender system based on social network of users. We implemented our proposed recommender system using a hashing technique to take advantage of parallel access to the items rated highly by users. To validate our recommendation method, we performed experiments on a real-world data set. The experimental results demonstrate the effectiveness of the proposed recommender system.

Keywords

Recommender system Big data Hashing Concurrent recommendation generation 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Rachael Chertok
    • 1
  • Nicholas Cockcroft
    • 1
  • Sourav Dutta
    • 1
    Email author
  1. 1.Department of Computer ScienceRamapo College of New JerseyMahwahUSA

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