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arXiv · 2209.12766

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

Mengli Cheng·Yue Gao·Guoqiang Liu·HongSheng Jin·Xiaowen Zhang
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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.

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Mengli Cheng, Yue Gao, Guoqiang Liu, HongSheng Jin, Xiaowen Zhang. 2022-09-26. EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems. https://arxiv.org/abs/2209.12766

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