EasyRec: An Easy-to-Use, Extendable and Efficient Framework for Building Industrial Recommendation Systems
Mengli Cheng, Yue Gao, Guoqiang Liu, HongSheng Jin · Proceedings of the AAAI Conference on Artificial Intelligence · 2023
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 adapt to the ever-changing data distribution. The code is released: https://github.com/alibaba/EasyRec.