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AAAI 2023

EasyRec: An Easy-to-Use, Extendable and Efficient Framework for Building Industrial Recommendation Systems

System Paper Demonstrations Artificial Intelligence

Abstract

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.

Authors

Keywords

  • Distributed Training
  • Hyperparameter Optimization
  • Large Scale
  • Recommedation Framework

Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
1007140033091659120