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

arXiv: https://arxiv.org/abs/2209.12766 · HTML: https://mlsanity.com/paper/2209.12766/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 17 references that are in the map.
- First posted on arXiv 26 Sep 2022.

## Builds on (most cited first, 6 of 6)

- [DeepFM: A Factorization-Machine based Neural Network for CTR Prediction](https://mlsanity.com/paper/1703.04247/) (2017)
- [Deep Interest Network for Click-Through Rate Prediction](https://mlsanity.com/paper/1706.06978/) (2017)
- [Multi-Interest Network with Dynamic Routing for Recommendation at Tmall](https://mlsanity.com/paper/1904.08030/) (2019)
- [Open Benchmarking for Click-Through Rate Prediction](https://mlsanity.com/paper/2009.05794/) (2020)
- [Towards a Better Tradeoff between Effectiveness and Efficiency in Pre-Ranking: A Learnable Feature Selection based Approach](https://mlsanity.com/paper/2105.07706/) (2021)
- [TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks](https://mlsanity.com/paper/1708.02637/) (2017)

## Built on by (most cited first, 3 of 3)

- [Arithmetic Feature Interaction Is Necessary for Deep Tabular Learning](https://mlsanity.com/paper/2402.02334/) (2024)
- [UFGraphFR: Graph Federation Recommendation System based on User Text description features](https://mlsanity.com/paper/2501.08044/) (2025)
- [ORBIT -- Open Recommendation Benchmark for Reproducible Research with Hidden Tests](https://mlsanity.com/paper/2510.26095/) (2025)

## Abstract (arXiv)

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.