Deep Recommenders
Deep Recommenders is an open-source recommendation system algorithm library
built by tf.estimator
and tf.keras
that the advanced APIs of TensorFlow.
🤗️ This Library mainly used for self-learning and improvement,
but also hope to help friends and classmates who are interested in the recommendation system to make progress together!
Models
Ranking
- FM
[Estimator]
Factorization Machines, Osaka, 2010
- FFM
Field-aware Factorization Machines for CTR Prediction, RecSys, 2016
- LS-PLM
Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction, Alibaba, 2017
- WDL
[Estimator]
Wide & Deep Learning for Recommender Systems, Google, DLRS, 2016
- PNN
Product-based Neural Networks for User Response Prediction, IEEE, 2016
- FNN
[Estimator]
Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction, RayCloud, ECIR, 2016
- NFM
Neural Factorization Machines for Sparse Predictive Analytics, SIGIR, 2017
- AFM
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks, IJCAI, 2017
- DeepFM
[Estimator]
[Keras]
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction, Huawei, IJCAI, 2017
- DCN
Deep & Cross Network for Ad Click Predictions, Google, KDD, 2017
- xDeepFM
xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems, Microsoft, KDD, 2018
- DIN
Deep Interest Network for Click-Through Rate Prediction, Alibaba, KDD, 2018
- DIEN
Deep Interest Evolution Network for Click-Through Rate Prediction, Alibaba, AAAI, 2019
- DLRM
Deep Learning Recommendation Model for Personalization and Recommendation Systems, Facebook, 2019
Retrieval
- DSSM
Learning Deep Structured Semantic Models for Web Search using Clickthrough Data, Microsoft, CIKM, 2013
- YoutubeNet
Deep Neural Networks for YouTube Recommendations, Google, RecSys, 2016
- SBCNM
Sampling-Bias-Corrected Neural Modeling for Large Corpus Item Recommendations, Google, RecSys, 2019
- EBR
Embedding-based Retrieval in Facebook Search, Facebook, KDD, 2020
- Item2Vec
Item2Vec: Neural Item Embedding for Collaborative Filtering, Microsoft, MLSP, 2016
- Airbnb
Real-time Personalization using Embeddings for Search Ranking at Airbnb, Airbnb, KDD, 2018
- DeepWalk
DeepWalk: Online Learning of Social Representations, StonyBrook, KDD, 2014
- EGES
Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba, Alibaba, KDD, 2018
- GCN
[Keras]
Semi-Supervised Classification with Graph Convolutional Networks, ICLR, 2017
- GraphSAGE
Inductive Representation Learning on Large Graphs, NIPS, 2017
- PinSage
Graph Convolutional Neural Networks for Web-Scale Recommender Systems, Pinterest, KDD, 2018
- IntentGC
IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation, Alibaba, KDD, 2019
- GraphTR
Graph Neural Network for Tag Ranking in Tag-enhanced Video Recommendation, Tencent, CIKM, 2020
Multi-task learning
NLP
Supports
Modules |
TensorFlow |
deep_recommenders.estimator |
|
deep_recommenders.keras |
|
License
Apache License 2.0