推荐系统论文及其源代码收集（持续更新）
大家也许跟我有同样的感受，在每次找到感兴趣的论文时，总是很难找到其对应的源码。
于是我将搜过的关于推荐系统的论文和源代码连接分享在这里，希望能帮到大家：）
1.Metric Factorization: Recommendation beyond Matrix Factorization
论文：https://www.researchgate.net/publication/325570047_Metric_Factorization_Recommendation_beyond_Matrix_Factorization
代码：https://github.com/cheungdaven/metricfactorization
2.Collaborative Memory Network for Recommendation Systems
论文：https://arxiv.org/pdf/1804.10862.pdf
代码：https://github.com/tebesu/CollaborativeMemoryNetwork
3.Evaluation of Session-based Recommendation Algorithms
论文：https://arxiv.org/pdf/1803.09587.pdf
代码：https://www.dropbox.com/sh/7qdquluflk032ot/AACoz2Go49q1mTpXYGe0gaANa?dl=0
4.Collaborative Filtering with Recurrent Neural Networks
论文：https://arxiv.org/pdf/1608.07400.pdf
代码：https://github.com/rdevooght/sequence-based-recommendations
5.Long and Short-Term Recommendations with Recurrent Neural Networks
论文：http://iridia.ulb.ac.be/~rdevooght/papers/UMAP__Long_and_short_term_with_RNN.pdf
代码：https://github.com/rdevooght/sequence-based-recommendations
6.RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems
论文：https://arxiv.org/pdf/1803.03467.pdf
代码：https://github.com/hwwang55/RippleNet
7.Content-Based Citation Recommendation
论文：http://aclweb.org/anthology/N18-1022
代码：https://github.com/allenai/citeomatic
8.Multi-Pointer Co-Attention Networks for Recommendation
论文：https://arxiv.org/pdf/1801.09251.pdf
代码：https://github.com/vanzytay/KDD2018_MPCN
9.ATRank: An Attention-Based User Behavior Modeling Framework for Recommendation
论文：https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/download/16216/16770
代码：https://github.com/jinze1994/ATRank
10.Deep Matrix Factorization Models for Recommender Systems
论文：https://www.ijcai.org/proceedings/2017/0447.pdf
代码：https://github.com/RuidongZ/Deep_Matrix_Factorization_Models
11.Perceiving the Next Choice with ComprehensiveTransaction Embeddings for Online Recommendation
论文：http://ecmlpkdd2017.ijs.si/papers/paperID293.pdf
代码：https://github.com/shoujin88/NTEM-model