QiaoXie / deep_ctr

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点击预估模型

1. Recall

算法 论文 公众号或知乎文章介绍
word2vec Efficient Estimation of Word Representations in Vector Space
YouTubeNet Deep Neural Networks for YouTube Recommendations 推荐系统召回模型之YouTubeNet
DSSM Sampling-Bias-Corrected Neural Modeling for Large Corpus Item Recommendations 实践DSSM召回模型
mind Multi-Interest Network with Dynamic Routing for Recommendation at Tmall 推荐系统召回模型之MIND用户多兴趣网络实践

2. Rank

算法 论文 公众号文章介绍
FFM Field-aware Factorization Machines for CTR Prediction FFM算法原理及Bi-FFM算法实现
wide_and_deep Wide & Deep Learning for Recommender Systems
NFM Neural Factorization Machines for Sparse Predictive Analytics NFM模型理论与实践
AFM Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks 注意力机制在深度推荐算法中的应用之AFM模型
DeepFM DeepFM: A Factorization-Machine based Neural Network for CTR Prediction DeepFM实践
BST Behavior sequence transformer for e-commerce recommendation in Alibaba Transformer 在美团搜索排序中的实践

3. 多任务 Rank

算法 论文 公众号文章介绍
esmm Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate ESMM多任务学习算法在推荐系统中的应用
MMoE Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts 多任务学习之MMOE模型

4. recall_search

算法 开源地址 公众号文章介绍
Annoy https://github.com/spotify/annoy Annoy最近邻检索技术之 “图片检索”

代码参考

https://github.com/shenweichen/DeepCTR

https://github.com/shenweichen/DeepMatch

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