An Evaluation of Generative Adversarial Networks for Collaborative Filtering.

Last update: Jan 19, 2022

Overview

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:

evaluation-cfgan: Contains the implementation of CFGAN and the experiments presented in the article.
recsys-framework: Contains the implementation of baselines, hyper-parameter tuning, and evaluation used in the article.
pdf: Contains a copy of the submitted article and additional material

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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Releases(v1.1.1-ecir-2022-camera-ready)

v1.1.1-ecir-2022-camera-ready(Jan 19, 2022)
Updates to README to include reference arXiv, github, and Zenodo links.

Updated CITATION file to refer to the PoliMi repo.

Source code(tar.gz)
Source code(zip)
v1.1.0-ecir-2022-camera-ready(Jan 5, 2022)

Source code(tar.gz)
Source code(zip)
v1.0.1-ecir-2022-camera-ready-prep(Jan 4, 2022)

Source code(tar.gz)
Source code(zip)
v1.0.0-ecir-2022-submission(Oct 22, 2021)

Source code(tar.gz)
Source code(zip)

An Evaluation of Generative Adversarial Networks for Collaborative Filtering.

Related tags

Overview

An Evaluation of Generative Adversarial Networks for Collaborative Filtering.

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Owner

Fernando Benjamín PÉREZ MAURERA

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