awesome-rec-papers
整理推薦系統必讀papers
必讀
-
[Youtube] Deep Neural Networks for YouTube Recommendations (Youtube 2016)
-
[Airbnb] Applying Deep Learning To Airbnb Search (Airbnb 2018)
-
[Pinterest] Personalized content blending In the Pinterest home feed (Pinterest 2016)
-
[Airbnb] Search Ranking and Personalization at Airbnb Slides (Airbnb 2018)
-
[Word2Vec] Distributed Representations of Words and Phrases and their Compositionality (Google 2013)
-
[Airbnb Embedding] Real-time Personalization using Embeddings for Search Ranking at Airbnb (Airbnb 2018)
-
[Alibaba Embedding] Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba (Alibaba 2018)
-
[Word2Vec] Efficient Estimation of Word Representations in Vector Space (Google 2013)
-
[LINE] LINE - Large-scale Information Network Embedding (MSRA 2015)
-
[DCN] Deep & Cross Network for Ad Click Predictions (Stanford 2017)
-
[Deep Crossing] Deep Crossing - Web-Scale Modeling without Manually Crafted Combinatorial Features (Microsoft 2016)
Conference
1、與推薦系統直接相關的會議
RecSys -The ACM Conference Series on Recommender Systems.
2、數據挖掘相關的會議
SIGKDD - The ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
WSDM - The International Conference on Web Search and Data Mining.
ICDM - The IEEE International Conference on Data Mining.
SDM -TheSIAM International Conference on Data Mining.
ECML-PKDD - The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
3、機器學習相關的會議
ICML - The International Conference on Machine Learning.
NIPS - The Conference on Neural Information Processing Systems
4、信息檢索相關的會議
SIGIR - The ACM International Conference on Research and Development in Information Retrieval
5、數據庫相關的會議
CIKM - The ACM International Conference on Information and Knowledge Management.
6、Web相關的會議
WWW - The International World Wide Web Conference.
7、人工智慧相關的會議
AAAI - The National Conference of the American Association for Artificial Intelligence.
IJCAI - The International Joint Conference on Artificial Intelligence.
ECAI -European Conference on Artificial Intelligence
UAI - The Conference on Uncertainty in Artificial Intelligence
大神
Yehuda Koren 個人主頁:Koren's HomePage
主要貢獻:Netflix Prize的冠軍隊成員,是推薦系統領域的大神級人物,曾就職雅虎,現就職於谷歌
代表文獻:Matrix Factorization Techniques For Recommender Systems
Steffen Rendle 個人主頁:Rendle's HomePage
主要貢獻:經典推薦演算法FM和BPR的提出者,現就職於谷歌
代表文獻:BPR: Bayesian Personalized Ranking from Implicit Feedback
Hao Ma 個人主頁:HaoMa's HomePage
主要貢獻:社會化推薦領域的大牛,提出了許多基於社會化推薦的有效演算法,現就職於微軟
代表文獻:SoRec: Social Recommendation Using Probabilistic Matrix Factorization
Julian McAuley 個人主頁:McAuley
主要貢獻:研究方向為社交網路、數據挖掘、推薦系統,現為加利福尼亞大學聖迭戈分校助理教授
代表文獻:Leveraging social connections to improve personalized ranking for collaborative filtering
郭貴冰 個人主頁:Guibing Guo's HomePage
主要貢獻:國內推薦系統大牛,創辦了推薦系統開源項目LibRec
代表文獻:TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings
Hao Wang 個人主頁:HaoWang's HomePage
主要貢獻:擅長運用深度學習技術提高推薦系統性能
代表文獻:Collaborative deep learning for recommender systems
何向南 個人主頁:Xiangnan He's Homepage
主要貢獻:運用深度學習技術提高推薦系統性能
代表文獻:Neural Collaborative Filtering
Robin Burke 個人主頁:rburke's HomePage
主要貢獻:混合推薦方向的大牛
代表文獻:Hybrid recommender systems: Survey and experiments
項亮 主要貢獻:國內推薦系統領域中理論與實踐並重的專家,Netflix Prize第二名
代表文獻:《推薦系統實踐》。
謝幸 個人主頁:Xing's Page
主要貢獻:專註於數據挖掘、社會計算等,擅長可解釋性推薦研究等。
代表文獻:A Survey on Knowledge Graph-Based Recommender Systems
Jiliang Tang 個人主頁:Jiliang's Page
主要貢獻:擅長利用社交網路分析相關技術提升推薦性能。
代表文獻:Social Recommendation: A Review
趙鑫 個人主頁:zhaoxin's HomePage
主要貢獻:國內推薦系統著名學者,側重利用自然語言處理技術來提升Top-N推薦性能
代表文獻:Improving Sequential Recommendation with Knowledge-enhanced Memory Networks
石川 個人主頁:shichuan's HomePage
主要貢獻:研究方向為異質信息網路上的推薦,提出了加權的異質信息相似度計算等
代表文獻:Semantic Path based Personalized Recommendation on Weighted Heterogeneous Information Networks
吳樂 個人主頁:Wu Le's HomePage
主要貢獻:研究方向為結合社交信息的推薦,提出了神經影響擴散模型等
代表文獻:A Neural Influence Diffusion Model for Social Recommendation
王鴻偉 個人主頁:Hongwei's Page
主要貢獻:關註於圖機器學習,聚焦在結合知識圖譜來進行推薦的領域。
代表文獻:Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation