深度学习推荐系统论文汇总

AutoRec

AutoRec: AutoRec: Autoencoders Meet Collaborative Filtering。

Deep Crossing

Deep Crossing: Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features。

NeuralCF

NeuralCF: Neural Collaborative Filtering。

PNN

PNN: Product-based Neural Networks for User Response Prediction。

Wide&Deep

Wide&Deep: Wide & Deep Learning for Recommender Systems。

Deep&Cross

Deep & Cross: Deep & Cross Network for Ad Click Predictions。

FNN

FNN: Deep Learning over Multi-field Categorical Data。

DeepFM

DeepFM: DeepFM: A Factorization-Machine based Neural Network for CTR Prediction。

NFM

NFM: Neural Factorization Machines for Sparse Predictive Analytics。

AFM

AFM: Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks。

DIN

DIN: Deep Interest Network for Click-Through Rate Prediction。

DIEN

DIEN: Deep Interest Evolution Network for Click-Through Rate Prediction。

DLRM

DLRM: Deep Learning Recommendation Model for Personalization and Recommendation Systems。

RPES

RPES: Real-time Personalization using Embeddings for Search Ranking at Airbnb。

YoutubeRec

YoutubeRec: Deep Neural Networks for YouTube Recommendations。

MIMN

MIMN: Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction。

ESMM

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

DICM

DICM: Image Matters: Visually modeling user behaviors using Advanced Model Server。

参考文献

1. http://users.cecs.anu.edu.au/~akmenon/papers/autorec/autorec-paper.pdf
2. https://www.kdd.org/kdd2016/papers/files/adf0975-shanA.pdf
3. https://arxiv.org/pdf/1708.05031.pdf
4. https://arxiv.org/pdf/1611.00144.pdf
5. https://arxiv.org/pdf/1606.07792.pdf
6. https://dl.acm.org/doi/pdf/10.1145/3124749.3124754
7. https://arxiv.org/pdf/1601.02376.pdf
8. https://www.ijcai.org/Proceedings/2017/0239.pdf
9. https://arxiv.org/pdf/1708.05027v1.pdf
10. https://arxiv.org/pdf/1708.04617.pdf
11. https://arxiv.org/pdf/1706.06978.pdf
12. https://arxiv.org/pdf/1809.03672.pdf
13. https://arxiv.org/pdf/1906.00091.pdf
14. https://astro.temple.edu/~tua95067/kdd2018.pdf
15. https://dl.acm.org/doi/pdf/10.1145/2959100.2959190
16. https://arxiv.org/pdf/1905.09248.pdf
17. https://arxiv.org/pdf/1804.07931.pdf
18. https://arxiv.org/pdf/1711.06505.pdf