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@@ -108,7 +108,7 @@ python -u tools/static_trainer.py -m models/rank/dnn/config.yaml # 静态图训
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| 匹配 | [MultiView-Simnet](models/match/multiview-simnet/) |||| x | >=2.1.0 | [WWW 2015][A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/frp1159-songA.pdf) |
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| 召回 | [TDM](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/treebased/tdm/) || >=1.8.0 || >=1.8.0 | [1.8.5](https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5) | [KDD 2018][Learning Tree-based Deep Model for Recommender Systems](https://arxiv.org/pdf/1801.02294.pdf) |
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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 | [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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