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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<Hailin Fu>. All Rights Reserved.

Licensed under the GNU License.

Contact

If you have any questions, please follow the following account:

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