EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems
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;...
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| Veröffentlicht in: | arXiv.org 2022-09 |
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| creator | Cheng, Mengli Gao, Yue Liu, Guoqiang Jin, HongSheng Zhang, Xiaowen |
| description | 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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| subjects | Algorithms Machine learning Modular design Optimization Recommender systems |
| title | EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems |
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