An Evaluation of Generative Adversarial Networks for Collaborative Filtering.

Related tags

Deep Learningevaluationcollaborative-filteringgenerative-adversarial-networkrecommender-systems
Overview

DOI

An Evaluation of Generative Adversarial Networks for Collaborative Filtering.

This repository was developed by Fernando B. Pérez Maurera. Fernando is a Ph.D. student at Politecnico di Milano.

This repository contains the source code of the following articles:

  • An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering. Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, and Paolo Cremonesi. Accepted to ECIR 2022.

See our website for more information on our research group. We are actively pursuing this research direction in evaluation and reproducibility, we are open to collaboration with other researchers. Follow our project on ResearchGate

This repo is divided in three folders:

You'll find instructions to install this project and run the experiments in the
README inside evaluation-cfgan, in fact, all commands must be run inside the evaluation-cfgan folder.

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Fernando Benjamín PÉREZ MAURERA
Computer Engineer & Ph.D. candidate in Information Technology
Fernando Benjamín PÉREZ MAURERA
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