论文标题

EasyRec:一个易于使用,可扩展和高效的框架,用于构建工业推荐系统

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

论文作者

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

论文摘要

我们提出了EasyRec,这是一个易于使用,可扩展和高效的推荐框架,用于构建工业推荐系统。我们的EasyRec框架在以下方面是优越的:首先,EasyRec采用模块化和可插入的设计模式来减少构建自定义模型的努力;其次,EasyRec实现了超参数优化和特征选择算法,以自动提高模型性能;第三,EasyRec应用在线学习,以快速适应不断变化的数据分布。该代码发布:https://github.com/alibaba/easyrec。

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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