大多文章都是关于NLP与推荐系统的。相关的不多。

Accepted paper list: Link

Time Series

• Dynamic Clustering with Discrete Time Event Prediction

  Karan Aggarwal: University of Minnesota; Georgios Theocharous: Adobe Research; Anup Rao: Yale University

Recurrent Neural Network

• A Deep Recurrent Survival Model for Unbiased Ranking

  Jiarui Jin: Shanghai Jiao Tong University; Yuchen Fang: Shanghai Jiao Tong University; Weinan Zhang: Shanghai Jiao Tong University; Kan Ren: Microsoft; Guorui Zhou: Alibaba; Jian Xu: Alibaba; Yong Yu: Shanghai Jiao Tong University; Jun Wang: University College London; Xiaoqiang Zhu: Alibaba; Kun Gai: Alibaba

Anomaly Detection

N/A

Sequence

• Dual Sequential Network for Temporal Sets Prediction

  Leilei Sun: Beihang University; Yansong Bai: Beihang University; Bowen Du: Beihang University; Chuanren Liu: University of Tennessee; Hui Xiong: Rutgers University; Weifeng Lv: Beihang University

• Crowdsourced Text Sequence Aggregation based on Hybrid Reliability and Representation

  Jiyi Li: University of Yamanashi

• Neural Hierarchical Factorization Machines for User’s Event Sequence Analysis

  Dongbo Xi: Institute of Computing Technology, Chinese Academy of Sciences; Fuzhen Zhuang: Institute of Computing Technology, Chinese Academy of Sciences; Bowen Song: Ant Financial Services Group; Yongchun Zhu: Institute of Computing Technology, Chinese Academy of Sciences; Shuai Chen: Ant Financial Services Group; Dan Hong: Ant Financial Services Group; Tao Chen: Ant Financial Group; Xi Gu: Ant Financial Services Group; Qing He: Institute of Computing Technology, CAS

Interpretable

• Towards Explainable Retrieval Models for Precision Medicine Literature Search

  Jiaming Qu: University of North Carolina at Chapel Hill; Jaime Arguello: University of North Carolina at Chapel Hill; Yue Wang: University of North Carolina at Chapel Hill

• The Curious Case of IR Explainability: Explaining Document Scores within and across Ranking Models

  Procheta Sen: Dublin City University; Manisha Verma: Verizon Media, New York, NY, USA; Debasis Ganguly: IBM Ireland Research Lab; Gareth Jones: Dublin City University

• Biomedical Information Retrieval Incorporating Knowledge Graph for Explainable Precision Medicine

  Zuoxi Yang: South China University of Technology; Shoubin Dong: South China University of Technology

Autoencoder

N/A

LSTM

N/A

Interpretable + Recommendation

• Explaining Recommendations in Heterogeneous Networks

  Azin Ghazimatin: Max Planck Institute for Informatics

• Fairness-Aware Explainable Recommendation over Knowledge Graphs

  Zuohui Fu: Rutgers University; Yikun Xian: Rutgers University; Ruoyuan Gao: Rutgers University; Jieyu Zhao: University of California, Los Angeles; Qiaoying Huang: Rutgers University; Yingqiang Ge: Rutgers University; Shuyuan Xu: Rutgers University; Shijie Geng: Rutgers University; Chirag Shah: University of Washington; Yongfeng Zhang: Rutgers University; Gerard de Melo: Rutgers University

• Try This Instead: Personalized and Interpretable Substitute Recommendation

  Tong Chen: The University of Queensland; Hongzhi Yin: The University of Queensland; Guanhua Ye: The University of Queensland; Zi Huang: The University of Queensland; Yang Wang: Hefei University of Technology; Meng Wang: Hefei University of Technology

• Neural Concept Map Generation for Effective Document Classification with Interpretable Structured Summarization

  Carl Yang: University of Illinois at Urbana-Champaign; Jieyu Zhang: University of Illinois at Urbana-Champaign; Haonan Wang: University of Illinois at Urbana-Champaign; Bangzheng Li: University of Illinois at Urbana-Champaign; Jiawei Han: University of Illinois at Urbana-Champaign

Sequence + Recommendation

• Sentiment-guided Sequential Recommendation

  Lin Zheng: Department of Computer Science, College of Engineering, Shantou University; Naicheng Guo: Department of Computer Science, College of Engineering, Shantou University; Weihao Chen: Department of Computer Science, College of Engineering, Shantou University; Jin Yu: Department of Computer Science, College of Engineering, Shantou University; Dazhi Jiang: Department of Computer Science, College of Engineering, Shantou University

• Sequential-based Adversarial Optimisation for Personalised Top-N Item Recommendation

  Jarana Manotumruksa: University College London; Emine Yilmaz: University College London

• Bridging Hierarchical and Sequential Context Modeling for Question-driven Extractive Answer Summarization

  Yang Deng: The Chinese University of Hong Kong; Wenxuan Zhang: The Chinese University of Hong Kong; Yaliang Li: Alibaba Group; Min Yang: The Chinese Academy of Sciences; Wai Lam: The Chinese University of Hong Kong; Ying Shen: Sun Yat-Sen University

• Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation

  Fajie Yuan: Tencent; Xiangnan He: University of Science and Technology of China; Alexandros Karatzoglou: Google; Liguang Zhang: Tencent

• Time Matters: Sequential Recommendation with Complex Temporal Information

  Wenwen Ye: Tsinghua University; Shuaiqiang Wang: JD.COM; Xu Chen: Tsinghua University; Xuepeng Wang: JD.COM; Zheng Qin: Tsinghua University; Dawei Yin: Baidu Inc.

• Group-Aware Long- and Short-Term Graph Representation Learning for Sequential Group Recommendation

  Wen Wang: East China Normal University; Wei Zhang: East China Normal University; Jun Rao: Search Product Center, WeChat Search Application Department, Tencent; Zhijie Qiu: Search Product Center, WeChat Search Application Department, Tencent; Bo Zhang: Search Product Center, WeChat Search Application Department, Tencent; Leyu Lin: Search Product Center, WeChat Search Application Department, Tencent; Hongyuan Zha: Georgia Institute of Technology

• KERL: A Knowledge-Guided Reinforcement Learning Model for Sequential Recommendation

  Pengfei Wang: Beijing University of Posts and Telecommunications; Yu Fan: Beijing University of Posts and Telecommunications; Long Xia: School of Information Technology, York University; Wayne Xin Zhao: School of Information, Renmin University of China; Shaozhang Niu: BUPT; Jimmy Huang: School of Information Technology, York University

• Sequential Recommendation with Self-attentive Multi-adversarial Network

  Ruiyang Ren: Renmin University of China; Zhaoyang Liu: Alibaba Group; Yaliang Li: Alibaba Group; Wayne Xin Zhao: Renmin University of China; Hui Wang: Renmin University of China; Bolin Ding: Alibaba Group; Ji-Rong Wen: Renmin University of China

• A General Network Compression Framework for Sequential Recommender Systems

  Yang Sun: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Fajie Yuan: Tencent; Min Yang: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Guoao Wei: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Zhou Zhao: Zhejiang University; Duo Liu: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences

• Next-item Recommendation with Sequential Hypergraphs

  Jianling Wang: Texas A&M University; Kaize Ding: Arizona State University; Liangjie Hong: Etsy Inc.; Huan Liu: Arizona State University; James Caverlee: Texas A&M University