Papers › EasyRec: An easy-to-use, extendable and efficient framework for building industrial...

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

26 Sep 2022arXiv:2209.12766archive 2025-07-28

Mengli Cheng, Yue Gao, Guoqiang Liu, Hongsheng Jin, Xiaowen Zhang

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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Recommendation Systemsfeature selection

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Capsule NetworkDeepWalkFeature SelectionHPOLayer NormalizationLinear LayerMulti-Head AttentionODLTransformer

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