在此推荐一个收集基于自然语言处理的推荐系统论文的Github仓库，该仓库收集并整理了关于自然语言处理与推荐系统相结合的若干研究方向，具体的包括综述论文、基于知识图谱的推荐系统、文字广告生成、对话推荐系统、可解释性推荐系统、上下文感知的推荐系统等，有需要的朋友可以参考所提到的具体论文。

仓库地址：https://github.com/THUDM/NLP4Rec-Papers

以下为仓库具体内容：

Paper Collection of NLP for Recommender System

Recent literatures explore the intersection of natural language processing and recommender systems.

This is a collection of research papers on this topic. The Papers are sorted by time. Any suggestions and pull requests are welcome.

Overview

Review Papers
Research Papers

KG for Recommendation
Text Ad Generation
Conversational Recommendation
Explainable Recommendation
Text Recommendation
Context-aware Recommendation

Review Papers

Critiquing-based recommenders: survey and emerging trends. Li Chen, Pearl Pu. UMUAI 2012.
Explainable Recommendation: A Survey and New Perspectives. Yongfeng Zhang, Xu Chen. 2018.

Research Papers

KG for Recommendation

Personalized Entity Recommendation: A Heterogeneous Information Network Approach. Xiao Yu, Xiang Ren, Yizhou Sun, Quanquan Gu, Bradley Sturt, Urvashi Khandelwal, Brandon Norick, Jiawei Han. WSDM 2014. UIUC.
Collaborative Knowledge Base Embedding for Recommender Systems. Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, Wei-Ying Ma. KDD 2016. Microsoft Research.
Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks. Huan Zhao, Quanming Yao, Jianda Li, Yangqiu Song, Dik Lun Lee. KDD 2017.
Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks. Jin Huang, Wayne Xin Zhao, Hongjian Dou, Ji-Rong Wen, and Edward Y. Chang. SIGIR 2018.
RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems. Hongwei Wang, Fuzheng Zhang, Jialin Wang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo. CIKM 2018. SJTU.
Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation. Hongwei Wang, Fuzheng Zhang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo. WWW 2019. SJTU.
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph. Weizhi Ma, Min Zhang, Yue Cao, Woojeong Jin, Chenyang Wang, Yiqun Liu, Shaoping Ma, Xiang Ren. WWW 2019.
KGAT: Knowledge Graph Attention Network for Recommendation. Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, Tat-Seng Chua. KDD 2019. NUS.
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation. Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, Yongfeng Zhang. SIGIR 2019.

Text Ad Generation

Neural Rating Regression with Abstractive Tips Generation for Recommendation. Piji Li, Zihao Wang, Zhaochun Ren, Lidong Bing, Wai Lam. SIGIR 2017. CUHK.
Generating Better Search Engine Text Advertisements with Deep Reinforcement Learning. John Hughes, Keng-Hao Chang and Ruofei Zhang. KDD 2019. Microsoft.
Towards Knowledge-Based Personalized Product Description Generation in E-commerce. Qibin Chen*, Junyang Lin*, Yichang Zhang, Hongxia Yang, Jingren Zhou, Jie Tang. KDD 2019. Alibaba.
Long and Diverse Text Generation with Planning-based Hierarchical Variational Model. Zhihong Shao, Minlie Huang, Jiangtao Wen, Wenfei Xu, Xiaoyan Zhu. EMNLP 2019. Tsinghua.
Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce. Jian-Guo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Xiuming Pan, Yu Gong, Philip S. Yu. NAACL-HLT 2019. Alibaba.

Conversational Recommendation

Deep Dialogue vs Casual Conversation in Recommender Systems. Lorraine McGinty, Barry Smyth. 2002.
A Personalized System for Conversational Recommendations. Cynthia A. Thompson, Mehmet H. Göker, Pat Langley. JAIR 2004.
Improving Recommender Systems with Adaptive Conversational Strategies. Tariq Mahmood, Francesco Ricci. HT 2009.
Critiquing-based recommenders: survey and emerging trends. Li Chen, Pearl Pu. UMUAI 2012.
Conversational Recommendation to Avoid the Cold-start Problem. F. Benito-Picazo, M. Enciso, C. Rossi and A. Guevara. CMMSE 2016.
Towards Conversational Recommender Systems. Konstantina Christakopoulou, Filip Radlinski, Katja Hofmann. KDD 2016. Microsoft.
Conversational Recommender System. Yueming Sun, Yi Zhang. SIGIR 2018. UCSC.
Towards Deep Conversational Recommendations. Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, and Chris Pal. NeurIPS 2018. Element AI.
Converse-Et-Impera: Exploiting Deep Learning and Hierarchical Reinforcement Learning for Conversational Recommender Systems. Claudio Greco, Alessandro Suglia, Pierpaolo Basile, and Giovanni Semeraro. AIIA 2019.
Towards Knowledge-Based Recommender Dialog System. Qibin Chen, Junyang Lin, Yichang Zhang, Ming Ding, Yukuo Cen, Hongxia Yang, Jie Tang. EMNLP 2019. Alibaba.
Deep Conversational Recommender in Travel. Lizi Liao, Ryuichi Takanobu, Yunshan Ma, Xun Yang, Minlie Huang, Tat-Seng Chua. arXiv preprint. NUS.

Explainable Recommendation

Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis. Yongfeng Zhang,Guokun Lai, Min Zhang, Yi Zhang, Yiqun Liu,Shaoping Ma. SIGIR 2014. Tsinghua.
Who Also Likes It? Generating the Most Persuasive Social Explanations in Recommender Systems. Beidou Wang, Martin Ester, Jiajun Bu, Deng Cai. AAAI 2014. ZJU.
TriRank: Review-aware Explainable Recommendation by Modeling Aspects. Xiangnan He, Tao Chen, Min-Yen Kan, Xiao Chen. CIKM 2015. NUS.
Crowd-Based Personalized Natural Language Explanations for Recommendations. Shuo Chang, F. Maxwell Harper, Loren Terveen. RecSys 2016.
Social Collaborative Viewpoint Regression with Explainable Recommendations. Zhaochun Ren, Shangsong Liang, Piji Li, Shuaiqiang Wang, Maarten de Rijke. WSDM 2017.
Explainable Entity-based Recommendations with Knowledge Graphs. Rose Catherine, Kathryn Mazaitis, Maxine Eskenazi, William Cohen. RecSys 2017.
Why I like it: Multi-task Learning for Recommendation and Explanation. Yichao Lu, Ruihai Dong, Barry Smyth. RecSys 2018.
TEM: Tree-enhanced Embedding Model for Explainable Recommendation. Xiang Wang, Xiangnan He, Xiangnan He, Liqiang Nie, Tat-Seng Chua. WWW 2018. NUS.
Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation. Qingyao Ai, Vahid Azizi, Xu Chen, and Yongfeng Zhang. Algorithms 2018.
Explainable Recommendation: A Survey and New Perspectives. Yongfeng Zhang, Xu Chen. 2018.
Explainable Recommendation Through Attentive Multi-View Learning. Jingyue Gao, Xiting Wang, Yasha Wang, Xing Xie. AAAI 2019. Microsoft Research Asia.
Explainable Reasoning over Knowledge Graphs for Recommendation. Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, Tat-Seng Chua. AAAI 2019. NUS.
A Reinforcement Learning Framework for Explainable Recommendation. Xiting Wang, Yiru Chen, Jie Yang, Le Wu, Zhengtao Wu, Xing Xie. ICDM 2018. Microsoft Research Asia.
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation. Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, Yongfeng Zhang. SIGIR 2019.

Text Recommendation

Ask the GRU: Multi-Task Learning for Deep Text Recommendations. Trapit Bansal, David Belanger, Andrew McCallum. RecSys 2016.
Embedding-based News Recommendation for Millions of Users. Shumpei Okura, Yukihiro Tagami, Shingo Ono, and Akira Tajima. KDD 2017.
DKN: Deep Knowledge-Aware Network for News Recommendation. Hongwei Wang, Fuzheng Zhang, Xing Xie, Minyi Guo. WWW 2018.
DRN: A Deep Reinforcement Learning Framework for News Recommendation. Guanjie Zheng, Fuzheng Zhang, Zihan Zheng, Yang Xiang, Nicholas Jing Yuan, Xing Xie, Zhenhui Li. WWW 2018.
Neural News Recommendation with Long- and Short-term User Representations. Mingxiao An, Fangzhao Wu, Chuhan Wu, Kun Zhang, Zheng Liu, Xing Xie. ACL 2019.
NPA: Neural News Recommendation with Personalized Attention. Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie. KDD 2019.
Neural News Recommendation with Attentive Multi-View Learning. Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie. IJCAI 2019.

Context-aware Recommendation

Cross-domain Collaboration Recommendation. Jie Tang, Sen Wu, Jimeng Sun, Hang Su. KDD 2012.
A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems. Ali Elkahky, Yang Song, Xiaodong He. WWW 2015. Microsoft Research.
Deep Neural Networks for YouTube Recommendations. Paul Covington, Jay Adams, Emre Sargin. RecSys 2016. Google.
Joint Deep Modeling of Users and Items Using Reviews for Recommendation. Lei Zheng, Vahid Noroozi, Philip S. Yu. WSDM 2017. UIUC.