A new Modular, Scalable, Configurable, Easy-to-Use and Extend infrastructure for Deep Learning based Recommendation.
Project description
DeePray (深度祈祷): A new Modular, Scalable, Configurable, Easy-to-Use and Extend infrastructure for Deep Learning based Recommendation.
Let's Get Started! https://deepray.readthedocs.io/en/latest/
Models List
| Titile | Booktitle | Resources |
|---|---|---|
| FM: Factorization Machines | ICDM'2010 | [pdf] [code] |
| FFM: Field-aware Factorization Machines for CTR Prediction | RecSys'2016 | [pdf] [code] |
| FNN: Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction | ECIR'2016 | [pdf][code] |
| PNN: Product-based Neural Networks for User Response Prediction | ICDM'2016 | [pdf][code] |
| Wide&Deep: Wide & Deep Learning for Recommender Systems | DLRS'2016 | [pdf][code] |
| AFM: Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks | IJCAI'2017 | [pdf][code] |
| NFM: Neural Factorization Machines for Sparse Predictive Analytics | SIGIR'2017 | [pdf][code] |
| DeepFM: DeepFM: A Factorization-Machine based Neural Network for CTR Prediction[C] | IJCAI'2017 | [pdf] [code] |
| DCN: Deep & Cross Network for Ad Click Predictions | ADKDD'2017 | [pdf] [code] |
| xDeepFM: xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems | KDD'2018 | [pdf] [code] |
| DIN: DIN: Deep Interest Network for Click-Through Rate Prediction | KDD'2018 | [pdf] [code] |
| DIEN: DIEN: Deep Interest Evolution Network for Click-Through Rate Prediction | AAAI'2019 | [pdf] [code] |
| DSIN: Deep Session Interest Network for Click-Through Rate Prediction | IJCAI'2019 | [pdf][code] |
| AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks | CIKM'2019 | [pdf][code] |
| FLEN: Leveraging Field for Scalable CTR Prediction | AAAI'2020 | [pdf][code] |
| DFN: Deep Feedback Network for Recommendation | IJCAI'2020 | [pdf][code] |
How to build your own model with DeePray
Inheriting BaseCTRModel class from from deepray.model.model_ctr, and implement your own build_network() method!
Contribution
DeePray is still under development, and call for contributions!
* Hailin Fu (`Hailin <https://github.com/fuhailin>`)
* Call for contributions!
License
Copyright (c) Copyright © 2020 The DeePray Authors. All Rights Reserved.
Licensed under the GNU License.
Contact
If you have any questions, please follow the following account:
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