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All Projects → mJackie → Recsys

mJackie / Recsys

计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估

Labels

machine-learningrecommender-systemrecommendation-system

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推荐系统/计算广告/机器学习/CTR预估资料汇总

License Update Progress SayThanks Travis

说明：本仓库主要汇集推荐系统/计算广告/机器学习/CTR预估相关学习资料，欢迎一起补充更新👼

更多前沿技术文章，欢迎移步 -> 精选文章

RoadMap

推荐系统

计算广告

统计学习模型

技术文章

实践工具

深度学习模型

技术文章

实践代码

相关比赛

CriteoDisplayAdvertisingChallenge

AvazuClickThroughRatePrediction

2018 IJCAI 阿里妈妈搜索广告转化预测

2018腾讯广告算法大赛

技术博客

经典论文清单

筛选文章的标准：前沿或者经典的，工程导向的，google、阿里、facebook等一线互联网公司出品的：

Wide & Deep Learning for Recommender Systems

google 的 wide&deep，必看论文，经典到难以附加

DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction

华为对wide&deep的改进，加了wide层的交叉项。如今工业界的主流模型

Practical lessons from predicting clicks on ads at facebook

facebook GBDT+LR的经典方案。虽然如今已不是主流方案，但论文中的思想很值得学习。

Deep Neural Networks for YouTube Recommendations

介绍了Youtube推荐系统工业界架构与方案，经典必看

Real-time Personalization using Embeddings for Search Ranking at Airbnb

KDD2018 best paper，Embedding 必看论文，非常经典

Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate

阿里的多目标学习经典方案，同时优化CTR & CVR

Real-time Personalization using Embeddings for Search Ranking at Airbnb

介绍了 airbnb 搜索排序模型的演进，工业性质很强，值得参考

搜索引擎点击模型综述

清华马少平团队的文章点击模型入门必看，搜索引擎点击模型综述

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