转载于 https://zhuanlan.zhihu.com/p/83103245

CTR

Collaborative Filtering

  • [WWW 17] Neural Collaborative Filtering
  • [SIGIR 18] Collaborative Memory Network for Recommendation Systems

Deep部分演进

  • [SIGIR 17] Neural Factorization Machines for Sparse Predictive Analytics
  • [IJCAI 17] Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
  • [ECIR 16] Factorization-supported Neural Network
  • [TOIS 18] Product-Based Neural Networks for User Response Prediction over Multi-Field Categorical Data
  • [RecSys 19] FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction
  • [KDD 18] Deep Interest Network for Click-through Rate Prediction
  • [AAAI 19] Deep Interest Evolution Network for Click-Through Rate Prediction
  • [IJCAI 19] Deep Session Interest Network for Click-Through Rate Prediction
  • [CIKM 19] AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

Wide部分演进

  • [IJCAI 17] DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
  • [KDD 17] Deep & Cross Network for Ad Click Predictions
  • [KDD 18] xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems
  • [WWW 19] Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction

强化学习

  • [WWW 17] DRN: A Deep Reinforcement Learning Framework for News Recommendation
  • [WSDM 19] Top-K Off-Policy Correction for a REINFORCE Recommender System
  • [IJCAI 19] Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology

知识图谱

  • [WWW 17] DKN: Deep Knowledge-Aware Network for News Recommendation
  • [CIKM 18] RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems

Embedding技术

  • [ICCCA 18] Item2Vec-Neural Item Embedding for Collaborative Filtering
  • [RecSys 16] Meta-Prod2Vec: Product Embeddings Using Side-Information for Recommendation
  • [KDD 18] Real-time Personalization using Embeddings for Search Ranking at Airbnb
  • [KDD 18] Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba
  • [WWW 19] NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
  • [IJCAI 19] ProNE: Fast and Scalable Network Representation Learning
赏

本文地址： http://easonlv.github.io/2019/09/28/工业界深度推荐系统与CTR预估论文/