Recommend system learning resources and learning notes
- [Earliest CF] Using Collaborative Filtering to Weave an Information Tapestry (PARC 1992)
- [ItemCF] Item-Based Collaborative Filtering Recommendation Algorithms (UMN 2001)
- [CF] Amazon Recommendations Item-to-Item Collaborative Filtering (Amazon 2003)
- [Bilinear] Personalized Recommendation on Dynamic Content Using Predictive Bilinear Models (Yahoo 2009)
- [MF] Matrix Factorization Techniques for Recommender Systems (Yahoo 2009)
- [FM]Factorization Machines2010
- [Recsys Intro] Recommender Systems Handbook (FRicci 2011)
- [Recsys Intro slides] Recommender Systems An introduction (DJannach 2014)
- [GBDT+LR](Practical Lessons from Predicting Clicks on Ads at Facebook 2014)
- [AutoRec] AutoRec: Autoencoders Meet Collaborative Filtering(2015)
- [Deep Crossing] Deep Crossing - Web-Scale Modeling without Manually Crafted Combinatorial Features (Microsoft 2016)
- [PNN] Product-based Neural Networks for User Response Prediction (SJTU 2016)
- [Wide&Deep] Wide & Deep Learning for Recommender Systems (Google 2016)
- [FNN] Deep Learning over Multi-field Categorical Data (UCL 2016)
- [NCF] Neural Collaborative Filtering (NUS 2017)
- [DCN] Deep & Cross Network for Ad Click Predictions (Stanford 2017)
- [DeepFM] A Factorization-Machine based Neural Network for CTR Prediction (HIT-Huawei 2017)
- [AFM] Attentional Factorization Machines - Learning the Weight of Feature Interactions via Attention Networks (ZJU 2017)