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推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction
- Addressing Marketing Bias in Product Recommendations.pdf
- BERT
- Transformer
- Adaptive Attention Span in Transformers.pdf
- Augmenting Self-attention with Persistent Memory.pdf
- BP-Transformer_Modelling Long-Range Context via Binary Partitioning.pdf
- Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling.pdf
- DiSAN_Directional Self-Attention Network for RNN_CNN-Free Language Understanding.pdf
- Generating Long Sequences with Sparse Transformers.pdf
- Insertion-based Decoding with automatically Inferred Generation Order.pdf
- Large Memory Layers with Product Keys.pdf
- Levenshtein Transformer.pdf
- Reformer_The Efficient Transformer.pdf
- Self-Attention with Relative Position Representations.pdf
- Star-Transformer.pdf
- Tensorized Embedding Layers for Efficient Model Compression.pdf
- Transformer-XL_Attentive Language Models Beyond a Fixed-Length Context.pdf
- Universal Transformers.pdf
- [ALBERT][arxiv 19][Google] ALBERT_A Lite BERT for Self-supervised Learning of Language Representations.pdf
- [BERT][arxiv 19][Google ]BERT_Pre-training of Deep Bidirectional Transformers for Language Understanding.pdf
- [ERNIE][arxiv 19][Baidu] ERNIE_Enhanced Representation through Knowledge Integration.pdf
- [T5][arxiv 19][Google] Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.pdf
- [XLNet][arxiv 19][Google] XLNet_Generalized Autoregressive Pretraining for Language Understanding.pdf
- CTR
- Extend
- CAN_Revisiting Feature Co-Action for Click-Through Rate Prediction.pdf
- DCN-M_Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems.pdf
- FuxiCTR_An Open Benchmark for Click-Through Rate Prediction.pdf
- [AAAI 20][Alibaba] Deep Time-Stream Framework for Click-Through Rate Prediction by Tracking Interest Evolution.pdf
- [AAAI 20][Alibaba] Rocket Launching_A Universal and Efficient Framework for Training Well-performing Light Net.pdf
- [Alibaba][SIM] Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction.pdf
- [AutoFIS][KDD 20][Huawei] AutoFIS_Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction.pdf
- [DMR][AAAI 20][Alibaba] Deep Match to Rank Model for Personalized Click-Through Rate Prediction.pdf
- [KDD 19][Alibaba][MIMN] Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction.pdf
- [MARN][WWW 20][Alibaba] Adversarial Multimodal Representation Learning for Click-Through Rate Prediction.pdf
- [MOBUIS][KDD 19] MOBIUS_Towards the Next Generation of Query-Ad Matching in Baidu’s Sponsored Search.pdf
- [PAL][RecSys 19][Huawei] PAL_A Position-bias Aware Learning Framework for CTR Prediction in Live Recommender Systems.pdf
- [PQR][AAAI 20][Tencent] Projective Quadratic Regression for Online Learning.pdf
- [SIGIR 20][Alibaba] Deep Interest with Hierarchical Attention Network for Click-Through Rate Prediction.pdf
- [WWW 20][Tencent]Field-aware Calibration_A Simple and Empirically Strong Method for Reliable Probabilistic Predictions.pdf
- [AFM][IJCAI 17] Attentional Factorization Machines - Learning the Weight of Feature Interactions via Attention Networks.pdf
- [AutoInt][CIKM 19] AutoInt_Automatic Feature Interaction Learning via Self-Attentive Neural Networks.pdf
- [DCN][KDD 17][Google] Deep & Cross Network for Ad Click Predictions.pdf
- [DIEN][AAAI 19][Alibaba] Deep Interest Evolution Network for Click-Through Rate Prediction.pdf
- [DIN][KDD 18][Alibaba] Deep Interest Network for Click-Through Rate Prediction.pdf
- [DSIN][IJCAI 19][Alibaba] Deep Session Interest Network for Click-Through Rate Prediction.pdf
- [DeepFM][IJCAI 17][Huawei] DeepFM_A Factorization-Machine based Neural Network for CTR Prediction.pdf
- [FGCNN][WWW 19][Huawei] Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction.pdf
- [FNN][ECIR 16] Deep Learning over Multi-field Categorical Data_A Case Study on User Response Prediction.pdf
- [FiBiNET][RecSys 19][Weibo] FiBiNET_Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction.pdf
- [NFM][SIGIR 17] Neural Factorization Machines for Sparse Predictive Analytics.pdf
- [PNN][TOIS 18] Product-based Neural Networks for User Response Prediction.pdf
- [WDL][DLRS 16][Google] Wide & Deep Learning for Recommender Systems.pdf
- [xDeepFM][KDD 18][Microsoft] xDeepFM_Combining Explicit and Implicit Feature Interactions for Recommender Systems.pdf
- Diversity
- [AAAI 20][Google] Pairwise Fairness for Ranking and Regression.pdf
- [CIKM 18][Google] Practical Diversified Recommendations on YouTube with Determinantal Point Processes.pdf
- [NeurIPS 18][Hulu] Fast Greedy MAP Inference for Determinantal Point Process to Improve Recommendation Diversity.pdf
- EE
- [LinUCB][WWW 10][Yahoo] A Contextual-Bandit Approach to Personalized News Article Recommendation.pdf
- Embedding
- Extend
- [MGQE][WWW 20][Google] Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems.pdf
- [SSL][Google] Self-supervised Learning for Deep Models in Recommendations.pdf
- [Airbnb Embedding][KDD 18][Airbnb] Real-time Personalization using Embeddings for Search Ranking at Airbnb.pdf
- [Alibaba Embedding][KDD 18][Alibaba] Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba.pdf
- [DeepWalk][KDD 14] DeepWalk- Online Learning of Social Representations.pdf
- [Etsy Embedding][DAPA-WSDM 19] Learning Item-Interaction Embeddings for User Recommendations.pdf
- [GraphSAGE][NIPS 17] Inductive Representation Learning on Large Graphs.pdf
- [KDD 20][FaceBook] Embedding-based Retrieval in Facebook Search.pdf
- [Node2vec][KDD 16] Node2vec_Scalable Feature Learning for Networks.pdf
- [Word2Vec][2013][Google] Efficient Estimation of Word Representations in Vector Space.pdf
- [Word2Vec][NIPS 13][Google] Distributed Representations of Words and Phrases and their Compositionality.pdf
- Graph
- Embedding
- [LINE][WWW 15][Microsoft] LINE_Large-scale Information Network Embedding.pdf
- [SDNE][KDD 16] Structural Deep Network Embedding.pdf
- [Struc2Vec][KDD 17] Struc2Vec_Learning Node Representations from Structural Identity.pdf
- Extend
- [DeepWak][KDD 14] DeepWalk_Online Learning of Social Representations.pdf
- [GraRep][CIKM 15] GraRep_Learning Graph Representations with Global Structural Information.pdf
- [HOPE][KDD 16] Asymmetric Transitivity Preserving Graph Embedding.pdf
- [NetMF][WSDM 18] Network Embedding as Matrix Factorization_Unifying DeepWalk, LINE, PTE, and node2vec.pdf
- [NetSMF][WWW 19] NetSMF_Large-Scale Network Embedding as Sparse Matrix.pdf
- [Node2Vec][KDD 16] Node2Vec_Scalable Feature Learning for Networks.pdf
- [ProNE][IJCAI 19] ProNE_Fast and Scalable Network Representation Learning.pdf
- NN
- Extend
- [GCN][ICLR 17] Semi-Supervised Classification with Graph Convolutional Networks.pdf
- [FastGCN][ICLR 18] FastGCN_Fast Learning with Graph Convolutional Networks via Importance Sampling.pdf
- [GAT][ICLR 18] Graph Attention Networks.pdf
- [KDD 20][Alibaba] Understanding Negative Sampling in Graph Representation Learning.pdf
- [GraphSAGE][NIPS 17] Inductive Representation Learning on Large Graphs.pdf
- [PinSage][KDD 18][Pinterest] Graph Convolutional Neural Networks for Web-Scale Recommender Systems.pdf
- KG
- Extend
- [AAAI 19][Ebay] Explainable Reasoning over Knowledge Graphs for Recommendation.pdf
- [ATBRG][SIGIR 20][Alibaba] ATBRG_Adaptive Target-Behavior Relational Graph Network for Effective Recommendation.pdf
- [DLP-KDD 19] An End-to-End Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation.pdf
- [KDD 19][Meituan] Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems.pdf
- [WWW 19][Microsoft] Knowledge Graph Convolutional Networks for Recommender Systems.pdf
- [WWW 19][Microsoft] Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation.pdf
- [KGAT][KDD 19] KGAT_Knowledge Graph Attention Network for Recommendation.pdf
- [RippleNet][CIKM 18] RippleNet_Propagating User Preferences on the Knowledge Graph for Recommender Systems.pdf
- KeyNote
- LICENSE
- MTL
- Extend
- Perceive Your Users in Depth- Learning Universal User Representations from Multiple E-commerce Tasks.pdf
- [ESM2][arxiv][Alibaba] Conversion Rate Prediction via Post-Click Behaviour Modeling.pdf
- [KDD 20][Alibaba] M2GRL_A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems.pdf
- [KDD 20][Alibaba] Multi-objective Optimization for Guaranteed Delivery in Video Service Platform.pdf
- [RecSys 19][Google] Recommending What Video to Watch Next_A Multitask Ranking System.pdf
- [AAAI 19][Google] SNR_Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning.pdf
- [AAAI 20] Learning Sparse Sharing Architectures for Multiple Tasks.pdf
- [ESMM][SIGIR 18][Alibaba] Entire Space Multi-Task Model_An Effective Approach for Estimating Post-Click Conversion Rate.pdf
- [KDD 20][Google] Multitask Mixture of Sequential Experts for User Activity Streams.pdf
- [MMoE][KDD 18][Google] Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts.pdf
- [RecSys 19][Alibaba] A Pareto-Efficient Algorithm for Multiple Objective Optimization in E-Commerce Recommendation.pdf
- Match
- Extend
- Next Item Recommendation with Self-Attention.pdf
- [CDL][KDD 15] Collaborative Deep Learning for Recommender Systems.pdf
- [LightRec][WWW 20][Microsoft]LightRec_a Memory and Search-Efficient Recommender System.pdf
- [MGNN][WWW 20][Tencent] Beyond Clicks_Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction.pdf
- [MOBIUS][KDD 19][Baidu] MOBIUS_Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search.pdf
- [RecSys 19][Google] Sampling-Bias-Corrected Neural Modeling for Large Corpus Item Recommendations.pdf
- [SIF][WWW 20][4Paradigm] Efficient Neural Interaction Function Search for Collaborative Filtering.pdf
- [DR][ByteDance] Deep Retrieval_An End-to-End Learnable Structure Model for Large-Scale Recommendations.pdf
- [DSSM][CIKM 13][Microsoft] Learning Deep Structured Semantic Models for Web Search using Clickthrough Data.pdf
- [JTM][NIPS 19] Joint Optimization of Tree-based Index and Deep Model for Recommender Systems.pdf
- [MIND][arxiv 19][Alibaba] Multi-Interest Network with Dynamic Routing for Recommendation at Tmall.pdf
- [NCF][WWW 17] Neural Collaborative Filtering.pdf
- [SDM][CIKM 19][Alibaba] Sequential Deep Matching Model for Online Large-scale Recommender System.pdf
- [TDM][KDD 18][Alibaba] Learning Tree-based Deep Model for Recommender Systems.pdf
- [YoutubeDNN][RecSys 16][Google] Deep Neural Networks for YouTube Recommendations.pdf
- deep learning for matching in search and recommendation book 2020.pdf
- README.md
- RL
- Extend
- [AAAI 19][Huawei] Large-scale Interactive Recommendation with Tree-structured Policy Gradient.pdf
- [AAAI 20][ByteDance] Deep Reinforcement Learning for Online Advertising in Recommender Systems.pdf
- [AAAI19][Alibaba] Virtual Taobao_Virtualizing Real-world Online Retail Environment for Reinforcement Learning.pdf
- [CIKM 18][Alibaba] Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising.pdf
- [HATCH][WWW 20][Didi]Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation.pdf
- [ICML 19][Alibaba] Generative Adversarial User Model for Reinforcement Learning Based Recommendation System.pdf
- [KDD 19][JD] Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems.pdf
- [RecSys18][JD] Deep Reinforcement Learning for Page-wise Recommendations.pdf
- [arxiv][ByteDance] Jointly Learning to Recommend and Advertise.pdf
- [DRN][WWW 18][Microsoft] DRN_A Deep Reinforcement Learning Framework for News Recommendation.pdf
- [IJCAI 19][Google] Reinforcement Learning for Slate-based Recommender Systems_A Tractable Decomposition and Practical Methodology.pdf
- [WSDM 19][Google] Top-K Off-Policy Correction for a REINFORCE Recommender System.pdf
- [WWW 20][Google] Off-policy Learning in Two-stage Recommender Systems.pdf
- Ranking
- [ACL 19][Microsoft] Neural News Recommendation with Long- and Short-term User Representations.pdf
- [BERT4Rec][CIKM 19][Alibaba] BERT4Rec_Sequential Recommendation with Bidirectional Encoder Representations from Transformer.pdf
- [BST][DLP-KDD 19][Alibaba] Behavior Sequence Transformer for E-commerce Recommendation in Alibaba.pdf
- [Choppy][SIGIR 20][Google] Choppy- Cut Transformer For Ranked List Truncation.pdf
- [FTRL][KDD 13][Google] Ad Click Prediction_a View from the Trenches.pdf
- [GBDT+LR][ADKDD 14][Facebook] Practical Lessons from Predicting Clicks on Ads at Facebook.pdf
- [ImageCTR][CIKM 18][Alibaba] Image Matters_Visually modeling user behaviors using Advanced Model Server.pdf
- [MDM 19] Sequence-Aware Recommendation with Long-Term and Short-Term Attention Memory Networks.pdf
- [SIGIR 20][Google] Feature Transformation for Neural Ranking Models.pdf
- [arxiv 18][Facebook] Collaborative Multi-modal Deep Learning for The Personalized Product Retrieval in Facebook Marketplace.pdf
- ReRank
- [PRM][RecSys 19][Alibaba] Personalized Re-ranking for Recommendation.pdf
- [SIGIR 18] Learning a Deep Listwise Context Model for Ranking Refinement.pdf
- Sequential
- [Transformer][ICDM 18] Self-Attentive Sequential Recommendation.pdf
- Extend
- [CMI][KDD 20][Alibaba] Controllable Multi-Interest Framework for Recommendation.pdf
- [SIGIR 20][Tencent] Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation.pdf
- [SIGIR 19][Alibaba] Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction.pdf
- [CNN][WSDM 18] Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding.pdf
- [GRU][CIKM 18] Recurrent Neural Networks with Top-k Gains for Session-based Recommendations.pdf
- [IJCAI 19] Sequential Recommender Systems_Challenges, Progress and Prospects.pdf
- UserModel
- avatar_wx.jpg
- deeprec_paper_structure.jpg
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