# DeepMatch **Repository Path**: cuigray/DeepMatch ## Basic Information - **Project Name**: DeepMatch - **Description**: No description available - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 1 - **Created**: 2024-07-10 - **Last Updated**: 2024-07-21 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # DeepMatch [![Python Versions](https://img.shields.io/pypi/pyversions/deepmatch.svg)](https://pypi.org/project/deepmatch) [![TensorFlow Versions](https://img.shields.io/badge/TensorFlow-1.9+/2.0+-blue.svg)](https://pypi.org/project/deepmatch) [![Downloads](https://pepy.tech/badge/deepmatch)](https://pepy.tech/project/deepmatch) [![PyPI Version](https://img.shields.io/pypi/v/deepmatch.svg)](https://pypi.org/project/deepmatch) [![GitHub Issues](https://img.shields.io/github/issues/shenweichen/deepmatch.svg )](https://github.com/shenweichen/deepmatch/issues) [![Documentation Status](https://readthedocs.org/projects/deepmatch/badge/?version=latest)](https://deepmatch.readthedocs.io/) ![CI status](https://github.com/shenweichen/deepmatch/workflows/CI/badge.svg) [![codecov](https://codecov.io/gh/shenweichen/DeepMatch/branch/master/graph/badge.svg)](https://codecov.io/gh/shenweichen/DeepMatch) [![Codacy Badge](https://app.codacy.com/project/badge/Grade/c5a2769ec35444d8958f6b58ff85029b)](https://www.codacy.com/gh/shenweichen/DeepMatch/dashboard?utm_source=github.com&utm_medium=referral&utm_content=shenweichen/DeepMatch&utm_campaign=Badge_Grade) [![Disscussion](https://img.shields.io/badge/chat-wechat-brightgreen?style=flat)](https://github.com/shenweichen/DeepMatch#disscussiongroup) [![License](https://img.shields.io/github/license/shenweichen/deepmatch.svg)](https://github.com/shenweichen/deepmatch/blob/master/LICENSE) 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))
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​ Shen Weichen ​

Alibaba Group

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Wang Zhe ​

Baidu Inc.

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​ Chen Leihui ​

Alibaba Group

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LeoCai

ByteDance

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​ Li Yuan

Tencent

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​ Yang Jieyu

Ant Group

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​ Meng Yifan

DeepCTR

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