PREA: Personalized Recommendation Algorithms Toolkit
Abstract
Recommendation systems are important business applications with significant economic impact. In recent years, a large number of algorithms have been proposed for recommendation systems. In this paper, we describe an open-source toolkit implementing many recommendation algorithms as well as popular evaluation metrics. In contrast to other packages, our toolkit implements recent state-of-the-art algorithms as well as most classic algorithms.
Cite
Text
Lee et al. "PREA: Personalized Recommendation Algorithms Toolkit." Machine Learning Open Source Software, 2012.Markdown
[Lee et al. "PREA: Personalized Recommendation Algorithms Toolkit." Machine Learning Open Source Software, 2012.](https://mlanthology.org/mloss/2012/lee2012jmlr-prea/)BibTeX
@article{lee2012jmlr-prea,
title = {{PREA: Personalized Recommendation Algorithms Toolkit}},
author = {Lee, Joonseok and Sun, Mingxuan and Lebanon, Guy},
journal = {Machine Learning Open Source Software},
year = {2012},
pages = {2699-2703},
volume = {13},
url = {https://mlanthology.org/mloss/2012/lee2012jmlr-prea/}
}