Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking, Post Ranking, Relevance, LLM and RL. Please cite our paper "Deep Learning to Rank in Industrial Search Engines, Recommender Systems, and Online Advertising - An Overview and New Perspectives" (TOIS 2026).
| Date | Stars |
|---|---|
| 2026-07-24 | 2556 |
| 2026-07-25 | 2557 |
| 2026-07-28 | 2557 |
| 2026-07-30 | 2557 |
| 2026-07-31 | 2565 |
| 2026-08-06 | 2571 |
Today
+6 stars today
This week
+14 stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.55%/day
## Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking (CTR/CVR prediction), Post-Ranking, Relevance-Ranking, LLM based ranking, Reinforcement Learning and so on. #### Please cite our paper: [Deep Learning to Rank in Industrial Search Engines, Recommender Systems, and Online Advertising - An Overview and New Perspectives](https://dl.acm.org/doi/full/10.1145/3797895), which was published in TOIS 2026. ## 00_Overview * [2026 (TOIS) [DLTR] Deep Learning to Rank in Industrial Search Engines, Recommender Systems, and Online Advertising - An Overview and New Perspectives](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/00_Overview/2026%20%28TOIS%29%20%5BDLTR%5D%20Deep%20Learning%20to%20Rank%20in%20Industrial%20Search%20Engines%2C%20Recommender%20Systems%2C%20and%20Online%20Advertising%20-%20An%20Overview%20and%20New%20Perspectives.pdf) <br /> ## 01_Embedding * [2013 (Google) (NIPS) [Word2vec] Distributed Representations of Words and Phrases and their Compositionality](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/01_Embedding/2013%20%28Google%29%20%28NIPS%29%20%5BWord2vec%5D%20Distributed%20Representations%20of%20Words%20and%20Phrases%20and%20their%20Compositionality.pdf) <br /> * [2014 (KDD) [DeepWalk] DeepWalk - online learning of social representations](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/01_Embedding/2014%20%28KDD%29%20%5BDeepWalk%5D%20%20DeepWalk%20-%20online%20learning%20of%20social%20representations.pdf) <br /> * [2015 (WWW) [LINE] LINE Large-scale Information Network Embedding](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/01_Embedding/2015%20%28WWW%29%20%5BLINE%5D%20LINE%20Large-scale%20Information%20Network%20Embedding.pdf) <br /> * [2016 (KDD) [Node2vec] node2vec - Scalable Feature Learning for Networks](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/01_Embedding/2016%20%28KDD%29%20%5BNode2vec%5D%20node2vec%20-%20Scalable%20Feature%20Learning%20for%20Networks.pdf) <br /> * [2017 (ICLR) [GCN] Semi-supervised Classification with Graph Convolutional Networks ](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/01_Embedding/2017%20%28ICLR%29%20%5BGCN%5D%20Semi-supervised%20Classification%20with%20Graph%20Convolutional%20Networks%20.pdf) <br /> * [2017 (KDD) [Struc2vec] struc2vec - Learning Node Representations from Structural Identity](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/01_Embedding/2017%20%28KDD%29%20%5BStruc2vec%5D%20struc2vec%20-%20Learning%20Node%20Representations%20from%20Structural%20Identity.pdf) <br /> * [2017 (NIPS) [GraphSAGE] Inductive Representation Learning on Large Graphs](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/01_Embedding/2017%20%28NIPS%29%20%5BGraphSAGE%5D%20Inductive%20Representation%20Learning%20on%20Large%20Graphs.pdf) <br /> * [2018 (Alibaba) (KDD) *[Alibaba Embedding] Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/01_Embedding/2018%20%28Alibaba%29%20%28KDD%29%20%2A%5BAlibaba%20Embedding%5D%20Billion-scale%20Commodity%20Embedding%20for%20E-commerce%20Recommendation%20in%20Alibaba.pdf) <br /> * [2018 (ICLR) [GAT] Graph Attention Networks](https://github.com/guyulongcs/Deep-Learning-for-Search-Recommendation-Advertisements/blob/master/01_Embedding/2018%20%28ICLR%29%20%5BGAT%5D%20%20Graph%20Attention%20Networks.pdf) <br /> * [2018 (Pinterest) (KDD) *[PinSage] Graph Convolutional Neural Networks for Web-Scale Recommender Systems](https://github.com/guyulongcs/Deep-Learning-
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matched fp:5d03b0b7f05cb4ae, topic:reinforcement-learning, readme:reinforcement learning
matched fp:5d03b0b7f05cb4ae, topic:deep-learning