EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems
This is an incremental improvement for developers and companies needing efficient recommendation systems.
The paper tackles the challenge of building industrial recommendation systems by introducing EasyRec, a framework that simplifies model creation, automates performance optimization, and adapts to changing data, resulting in a released open-source tool.
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.