https://github.com/shenweichen/DeepMatch

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.
https://github.com/shenweichen/DeepMatch

collaborative-filtering comirec dssm factorization-machines matching mind recommendation youtubednn

Last synced: about 1 month ago
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A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.

• Host: GitHub
• URL: https://github.com/shenweichen/DeepMatch
• Owner: shenweichen
• License: apache-2.0
• Created: 2020-04-06T04:07:33.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2024-05-14T09:35:43.000Z (12 months ago)
• Last Synced: 2024-10-29T15:33:43.582Z (6 months ago)
• Topics: collaborative-filtering, comirec, dssm, factorization-machines, matching, mind, recommendation, youtubednn
• Language: Python
• Homepage: https://deepmatch.readthedocs.io/en/latest/
• Size: 1.34 MB
• Stars: 2,224
• Watchers: 50
• Forks: 530
• Open Issues: 40
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

        
# DeepMatch

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DeepMatch is a deep matching model library for recommendations & advertising. It's easy to **train models** and to **export representation vectors** for user and item which can be used for **ANN search**.You can use any complex model with `model.fit()`and `model.predict()` .

Let's [**Get Started!**](https://deepmatch.readthedocs.io/en/latest/Quick-Start.html) or [**Run examples**](./examples/colab_MovieLen1M_YoutubeDNN.ipynb) !

## Models List

|                 Model                  | Paper                                                                                                                                                           |

| :------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------- |

|  FM  | [ICDM 2010][Factorization Machines](https://www.researchgate.net/publication/220766482_Factorization_Machines) |

| DSSM | [CIKM 2013][Deep Structured Semantic Models for Web Search using Clickthrough Data](https://www.microsoft.com/en-us/research/publication/learning-deep-structured-semantic-models-for-web-search-using-clickthrough-data/)    |

| YoutubeDNN     | [RecSys 2016][Deep Neural Networks for YouTube Recommendations](https://www.researchgate.net/publication/307573656_Deep_Neural_Networks_for_YouTube_Recommendations)            |

| NCF  | [WWW 2017][Neural Collaborative Filtering](https://arxiv.org/abs/1708.05031)       |

| SDM  | [CIKM 2019][SDM: Sequential Deep Matching Model for Online Large-scale Recommender System](https://arxiv.org/abs/1909.00385)  |

| MIND | [CIKM 2019][Multi-interest network with dynamic routing for recommendation at Tmall](https://arxiv.org/pdf/1904.08030)  |

| COMIREC | [KDD 2020][Controllable Multi-Interest Framework for Recommendation](https://arxiv.org/pdf/2005.09347.pdf)  |

## Contributors([welcome to join us!](./CONTRIBUTING.md))

  

    

      

        ​ 


        ​ Shen Weichen ​

        


        Alibaba Group  
​

      

      

         


         Wang Zhe ​

        
Baidu Inc.  
​

      

      

        ​ 


        ​ Chen Leihui ​

        


        Alibaba Group  
​

      

      

        ​ 


         LeoCai

         
  ByteDance   
​

      

      

        ​ 


        ​ Li Yuan

        
 Tencent    
​

      

      

        ​ 


        ​ Yang Jieyu

        
 Ant Group    
​

      

      

        ​ 


        ​ Meng Yifan

        
 DeepCTR    
​

      

    

  


## DisscussionGroup

- [Github Discussions](https://github.com/shenweichen/DeepMatch/discussions)

- Wechat Discussions

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