A new Recommendation Model for the User Clustering-Based Recommendation System

Authors

  • Aurimas Rapečka Vilnius University, Institute of Mathematics and Informatics
  • Gintautas Dzemyda Vilnius University, Institute of Mathematics and Informatics

DOI:

https://doi.org/10.5755/j01.itc.44.1.5931

Keywords:

recommendation systems, user clustering, user filtering algorithms

Abstract

The aim of this paper is to create a new recommendation model, that would evaluate peculiarities of user groups, and to examine experimentally the efficiency of user clustering in order to improve the recommendations. The research has disclosed dependencies of the efficiency of recommendations on the number of clusters. The new recommendation model is proposed here for the user clustering-based recommendation system.

DOI: http://dx.doi.org/10.5755/j01.itc.44.1.5931

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Published

2015-03-30

Issue

Section

Articles