Awesome-RecSys-Works

Papers and works on Recommendation System(RecSys) you must know

Survey Review

Titile	Booktitle	Authors	Resources
Deep Learning Based Recommender System: A Survey and New Perspectives	ACM Computing Surveys (CSUR)'2019	Shuai Zhang; Lina Yao; Aixin Sun; Yi Tay	[pdf]
Sequential Recommender Systems: Challenges, Progress and Prospects	IJCAI'2019	Shoujin Wang; Liang Hu; Yan Wang; Longbing Cao; Quan Z. Sheng; Mehmet Orgun	[pdf]
Real-time Personalization using Embeddings for Search Ranking at Airbnb	KDD'2018	Mihajlo Grbovic (Airbnb); Haibin Cheng (Airbnb)	[pdf]
Deep Neural Networks for YouTube Recommendations	RecSys '2016	Paul Covington(Google);Jay Adams(Google);Emre Sargin(Google)	[pdf]
The Netflix Recommender System: Algorithms, Business Value, and Innovation	ACM TMIS'2015	Carlos A. Gomez-Uribe(Netflix);Neil Hunt(Netflix)	[pdf]
MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu’s Sponsored Search	KDD ’19	Baidu Search Ads (Phoenix Nest)	[pdf]

Click-Through-Rate(CTR) Prediction

Titile	Booktitle	Resources
FM: Factorization Machines	ICDM'2010	[pdf] [code] [tffm] [fmpytorch]
libFM: Factorization Machines with libFM	ACM Trans'2012	[pdf] [code]
GBDT+LR: Practical Lessons from Predicting Clicks on Ads at Facebook	ADKDD'14	[pdf]
FFM: Field-aware Factorization Machines for CTR Prediction	RecSys'2016	[pdf] [code]
FNN: Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction	ECIR'2016	[pdf][Tensorflow]
PNN: Product-based Neural Networks for User Response Prediction	ICDM'2016	[pdf][Tensorflow]
Wide&Deep: Wide & Deep Learning for Recommender Systems	DLRS'2016	[pdf][Tensorflow][Blog]
AFM: Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks	IJCAI'2017	[pdf][Tensorflow]
NFM: Neural Factorization Machines for Sparse Predictive Analytics	SIGIR'2017	[pdf][Tensorflow]
DeepFM: DeepFM: A Factorization-Machine based Neural Network for CTR Prediction[C]	IJCAI'2017	[pdf] [code]
DCN: Deep & Cross Network for Ad Click Predictions	ADKDD'2017	[pdf] [Keras][Tensorflow]
xDeepFM: xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems	KDD'2018	[pdf] [Tensorflow]
DIN: DIN: Deep Interest Network for Click-Through Rate Prediction	KDD'2018	[pdf] [Tensorflow]
DIEN: DIEN: Deep Interest Evolution Network for Click-Through Rate Prediction	AAAI'2019	[pdf] [Tensorflow]
DSIN: Deep Session Interest Network for Click-Through Rate Prediction	IJCAI'2019	[pdf][Tensorflow]
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks	CIKM'2019	[pdf][Tensorflow]
FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction	RecSys '19	[pdf][Tensorflow]
DeepGBM:A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks	KDD'2019	[pdf][Tensorflow]
FLEN: Leveraging Field for Scalable CTR Prediction	AAAI'2020	[pdf][Tensorflow]
DFN: Deep Feedback Network for Recommendation	IJCAI'2020	[pdf][Tensorflow]
AutoDis: An Embedding Learning Framework for Numerical Features in CTR Prediction	KDD ’21	[pdf]

Retrieval

Titile	Booktitle	Resources
DSSM:Learning Deep Structured Semantic Models for Web Search using Clickthrough Data	CIKM'13	[pdf][TensorFlow]
EBR:Embedding-based Retrieval in Facebook Search	KDD'20	[pdf]
Deep Retrieval: Learning A Retrievable Structure for Large-Scale Recommendations	arXiv'20	[pdf]

Sequence-based Recommendations

Titile	Booktitle	Resources
GRU4Rec:Session-based Recommendations with Recurrent Neural Networks	ICLR'2016	[pdf][code]
DREAM:A Dynamic Recurrent Model for Next Basket Recommendation	SIGIR'2016	[pdf][code]
Long and Short-Term Recommendations with Recurrent Neural Networks	UMAP’2017	[pdf][Theano]
Time-LSTM:What to Do Next: Modeling User Behaviors by Time-LSTM	IJCAI'2017	[pdf] [code]
Caser:Personalized Top-N Sequential Recommendation via Convolutional Sequence EmbeddingCaser	WSDM'2018	[pdf] [code]
SASRec:Self-Attentive Sequential Recommendation	ICDM'2018	[pdf][code]
BERT4Rec:BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer	ACM WOODSTOCK’2019	[pdf][code]
SR-GNN: Session-based Recommendation with Graph Neural Networks	AAAI'2019	[pdf] [code]

Knowledge Graph

Titile	Booktitle	Resources
RippleNet: RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems	CIKM'2018	[pdf] [code]

Collaborative Filtering

Titile	Booktitle	Resources
UBCF:GroupLens: an open architecture for collaborative filtering of netnews	CSCW'1994	[pdf][code]
IBCF:Item-based collaborative filtering recommendation algorithms	WWW'2001	[pdf][code]
SVD:Matrix Factorization Techniques for Recommender Systems	Journal Computer'2009	[pdf][code]
SVD++:Factorization meets the neighborhood: a multifaceted collaborative filtering model	KDD'2008	[pdf][code]
PMF: Probabilistic Matrix Factorization	NIPS'2007	[pdf] [code]
CDL:Collaborative Deep Learning for Recommender Systems	KDD '2015	[pdf][code][PPT]
ConvMF:Convolutional Matrix Factorization for Document Context-Aware Recommendation	RecSys'2016	[pdf][code][zhihu][PPT]
NCF:Neural Collaborative Filtering	WWW '17	pdfcode

AutoML

Titile	Booktitle	Resources
AutoCTR:Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction	KDD'20	[pdf]

Other

DropoutNet: Addressing Cold Start in Recommender Systems. [pdf] [code]

Graph Neural Networks

Transfer Learning

Public Datasets

• KASANDR:KASANDR: A Large-Scale Dataset with Implicit Feedback for Recommendation (SIGIR 2017). [pdf] [KASANDR Data Set ]

Blogs

• Deep Learning Meets Recommendation Systems by Wann-Jiun

• Quora: Has there been any work on using deep learning for recommendation engines?.

Courses & Tutorials

• Recommender Systems Specialization Coursera

• Deep Learning for Recommender Systems by Balázs Hidasi. RecSys Summer School, 21-25 August, 2017, Bozen-Bolzano. Slides

• Deep Learning for Recommender Systems by Alexandros Karatzoglou and Balázs Hidasi. RecSys2017 Tutorial. Slides

Recommendation Systems Engineer Skill Tree

• Skill Tree pdf