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‎README.md‎

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@@ -109,6 +109,7 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # 静态图训
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| 召回 | [fasttext](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/fasttext/) | ✓ | ✓ | x | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [EACL 2017][Bag of Tricks for Efficient Text Classification](https://www.aclweb.org/anthology/E17-2068.pdf) |
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| 召回 | [MIND](models/recall/mind/) | ✓ | ✓ | x | x | 2.1.0 | [2019][Multi-Interest Network with Dynamic Routing for Recommendation at Tmall](https://arxiv.org/pdf/1904.08030.pdf) |
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| 召回 | [Word2Vec](models/recall/word2vec/) | ✓ | ✓ | ✓ | x | 2.1.0 | [NIPS 2013][Distributed Representations of Words and Phrases and their Compositionality](https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf) |
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| 召回 | [DeepWalk](models/recall/deepwalk/) | ✓ | ✓ | x | x | 2.1.0 | [SIGKDD 2014][DeepWalk: Online Learning of Social Representations](https://arxiv.org/pdf/1403.6652.pdf) |
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| 召回 | [SSR](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/ssr/) | ✓ | ✓ | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [SIGIR 2016][Multtti-Rate Deep Learning for Temporal Recommendation](http://sonyis.me/paperpdf/spr209-song_sigir16.pdf) |
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| 召回 | [Gru4Rec](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/gru4rec/) | ✓ | ✓ | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [2015][Session-based Recommendations with Recurrent Neural Networks](https://arxiv.org/abs/1511.06939) |
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| 召回 | [Youtube_dnn](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/youtube_dnn/) | ✓ | ✓ | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [RecSys 2016][Deep Neural Networks for YouTube Recommendations](https://static.googleusercontent.com/media/research.google.com/zh-CN//pubs/archive/45530.pdf) |
@@ -122,9 +123,10 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # 静态图训
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| 排序 | [FNN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/fnn/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [ECIR 2016][Deep Learning over Multi-field Categorical Data](https://arxiv.org/pdf/1601.02376.pdf) |
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| 排序 | [Deep Crossing](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/deep_crossing/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [ACM 2016][Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features](https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf) |
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| 排序 | [Pnn](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/pnn/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [ICDM 2016][Product-based Neural Networks for User Response Prediction](https://arxiv.org/pdf/1611.00144.pdf) |
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| 排序 | [DCN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/dcn/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [KDD 2017][Deep & Cross Network for Ad Click Predictions](https://dl.acm.org/doi/pdf/10.1145/3124749.3124754) |
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| 排序 | [DCN](models/rank/dcn/) | ✓ | ✓ | ✓ | x | 2.1.0 | [KDD 2017][Deep & Cross Network for Ad Click Predictions](https://dl.acm.org/doi/pdf/10.1145/3124749.3124754) |
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| 排序 | [NFM](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/nfm/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [SIGIR 2017][Neural Factorization Machines for Sparse Predictive Analytics](https://dl.acm.org/doi/pdf/10.1145/3077136.3080777) |
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| 排序 | [AFM](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/afm/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [IJCAI 2017][Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks](https://arxiv.org/pdf/1708.04617.pdf) |
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| 排序 | [DMR](models/rank/dmr/) | ✓ | ✓ | x | x | 2.1.0 | [AAAI 2020][Deep Match to Rank Model for Personalized Click-Through Rate Prediction](https://github.com/lvze92/DMR/blob/master/%5BDMR%5D%20Deep%20Match%20to%20Rank%20Model%20for%20Personalized%20Click-Through%20Rate%20Prediction-AAAI20.pdf) |
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| 排序 | [DeepFM](models/rank/deepfm/) | ✓ | ✓ | ✓ | x | 2.1.0 | [IJCAI 2017][DeepFM: A Factorization-Machine based Neural Network for CTR Prediction](https://arxiv.org/pdf/1703.04247.pdf) |
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| 排序 | [xDeepFM](models/rank/xdeepfm/) | ✓ | ✓ | ✓ | x | 2.1.0 | [KDD 2018][xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems](https://dl.acm.org/doi/pdf/10.1145/3219819.3220023) |
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| 排序 | [DIN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/din/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [KDD 2018][Deep Interest Network for Click-Through Rate Prediction](https://dl.acm.org/doi/pdf/10.1145/3219819.3219823) |

‎README_EN.md‎

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| Recall | [fasttext](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/fasttext/) | ✓ | ✓ | x | x |[1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [EACL 2017][Bag of Tricks for Efficient Text Classification](https://www.aclweb.org/anthology/E17-2068.pdf) |
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| Recall | [MIND](models/recall/mind/) | ✓ | ✓ | x | x | 2.1.0 | [2019][Multi-Interest Network with Dynamic Routing for Recommendation at Tmall](https://arxiv.org/pdf/1904.08030.pdf) |
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| Recall | [Word2Vec](models/recall/word2vec/) | ✓ | ✓ | ✓ | x | 2.1.0 | [NIPS 2013][Distributed Representations of Words and Phrases and their Compositionality](https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf) |
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| Recall | [DeepWalk](models/recall/deepwalk/) | ✓ | ✓ | x | x | 2.1.0 | [SIGKDD 2014][DeepWalk: Online Learning of Social Representations](https://arxiv.org/pdf/1403.6652.pdf) |
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| Recall | [SSR](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/ssr/) | ✓ | ✓ | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [SIGIR 2016][Multi-Rate Deep Learning for Temporal Recommendation](http://sonyis.me/paperpdf/spr209-song_sigir16.pdf) |
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| Recall | [Gru4Rec](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/gru4rec/) | ✓ | ✓ | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [2015][Session-based Recommendations with Recurrent Neural Networks](https://arxiv.org/abs/1511.06939) |
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| Recall | [Youtube_dnn](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/recall/youtube_dnn/) | ✓ | ✓ | ✓ | ✓ | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [RecSys 2016][Deep Neural Networks for YouTube Recommendations](https://static.googleusercontent.com/media/research.google.com/zh-CN//pubs/archive/45530.pdf) |
@@ -117,9 +118,10 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # Training wit
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| Rank | [FNN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/fnn/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [ECIR 2016][Deep Learning over Multi-field Categorical Data](https://arxiv.org/pdf/1601.02376.pdf) |
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| Rank | [Deep Crossing](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/deep_crossing/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [ACM 2016][Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features](https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf) |
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| Rank | [Pnn](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/pnn/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [ICDM 2016][Product-based Neural Networks for User Response Prediction](https://arxiv.org/pdf/1611.00144.pdf) |
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| Rank | [DCN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/dcn/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [KDD 2017][Deep & Cross Network for Ad Click Predictions](https://dl.acm.org/doi/pdf/10.1145/3124749.3124754) |
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| Rank | [DCN](models/rank/dcn/) | ✓ | ✓ | ✓ | x | 2.1.0 | [KDD 2017][Deep & Cross Network for Ad Click Predictions](https://dl.acm.org/doi/pdf/10.1145/3124749.3124754) |
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| Rank | [NFM](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/nfm/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [SIGIR 2017][Neural Factorization Machines for Sparse Predictive Analytics](https://dl.acm.org/doi/pdf/10.1145/3077136.3080777) |
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| Rank | [AFM](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/afm/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [IJCAI 2017][Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks](https://arxiv.org/pdf/1708.04617.pdf) |
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| Rank | [DMR](models/rank/dmr/) | ✓ | ✓ | x | x | 2.1.0 | [AAAI 2020][Deep Match to Rank Model for Personalized Click-Through Rate Prediction](https://github.com/lvze92/DMR/blob/master/%5BDMR%5D%20Deep%20Match%20to%20Rank%20Model%20for%20Personalized%20Click-Through%20Rate%20Prediction-AAAI20.pdf) |
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| Rank | [DeepFM](models/rank/deepfm/) | ✓ | ✓ | ✓ | x | 2.1.0 | [IJCAI 2017][DeepFM: A Factorization-Machine based Neural Network for CTR Prediction](https://arxiv.org/pdf/1703.04247.pdf) |
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| Rank | [xDeepFM](models/rank/xdeepfm/) | ✓ | ✓ | ✓ | x | 2.1.0 | [KDD 2018][xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems](https://dl.acm.org/doi/pdf/10.1145/3219819.3220023) |
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| Rank | [DIN](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rank/din/) | ✓ | ✓ | ✓ | x | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [KDD 2018][Deep Interest Network for Click-Through Rate Prediction](https://dl.acm.org/doi/pdf/10.1145/3219819.3219823) |

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