English

EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems

Information Retrieval 2022-09-27 v1 Artificial Intelligence

Abstract

We present EasyRec, an easy-to-use, extendable and efficient recommendation framework for building industrial recommendation systems. Our EasyRec framework is superior in the following aspects: first, EasyRec adopts a modular and pluggable design pattern to reduce the efforts to build custom models; second, EasyRec implements hyper-parameter optimization and feature selection algorithms to improve model performance automatically; third, EasyRec applies online learning to fast adapt to the ever-changing data distribution. The code is released: https://github.com/alibaba/EasyRec.

Keywords

Cite

@article{arxiv.2209.12766,
  title  = {EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems},
  author = {Mengli Cheng and Yue Gao and Guoqiang Liu and HongSheng Jin and Xiaowen Zhang},
  journal= {arXiv preprint arXiv:2209.12766},
  year   = {2022}
}

Comments

2 pages, 1 figures

R2 v1 2026-06-28T02:07:06.963Z