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Software . 2021
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EBCR: Empirical Bayes concordance ratio method to improve similarity measurement in memory-based collaborative filtering

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 11 Jan 2021Publisher:Zenodo
Authors: Ranwez, Vincent; Du, Yu; Sutton-Charani, Nicolas; Ranwez, Sylvie;
Code repository: https://github.com/dy2zyx/EBCR/tree/1.0.0

doi: 10.5281/zenodo.5013115 , 10.5281/zenodo.4431781

EBCR: Empirical Bayes concordance ratio method to improve similarity measurement in memory-based collaborative filtering

Abstract

This repository contains the source code of the proposed EBCR method, along with the datasets used and the evaluation results.

Related Organizations
Keywords

Collaborative filtering, Recommender system

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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