SIGIR｜乘风破浪的AI华人学者们
舞台已经搭好，就等“浪花”为学者们加油助力！
SIGIR 2020 上华人表现亮眼
下图为入选 5 篇以上的华人学者名单。
SIGIR 2020 上的华人明星
· Hierarchical Fashion Graph Network for Personalized Outfit Recommendation
· How to Retrain a Recommender System
· Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation
· Disentangled Representations for Graph-based Collaborative Filtering
· Lightening Graph Convolution Network for Recommendation
· Certifiable Robustness to Discrete Adversarial Perturbations for Factorization Machines
· Multi-behavior Recommendation with Graph Convolution Networks
· Modeling Personalized Item Frequency Information for Next-basket Recommendation
刘奕群
入选论文
· Make It a CHORUS: Context- and Knowledge-aware Item Modeling for Recommendation
· Investigating reading behavior in Fine-grained Relevance Judgment
· An analysis of BERT in document ranking
· Cascade or Recency: Constructing Better Evaluation Metrics for Session Search
· Beyond User Embedding Matrix: Learning to Hash for Modeling Large-Scale Users in Recommendation
· Preference-based Evaluation Metrics for Web Image Search
· Models Versus Satisfaction: Towards a Better Understanding of Evaluation Metrics
共有8篇论文入选
现为清华大学计算机系副教授。2003年于清华大学计算机科学与技术系获得博士学位，主要研究领域集中在信息检索，个性化推荐，用户行为分析和机器学习。
入选论文
· Jointly Non-Sampling Learning for Knowledge Graph Enhanced Recommendation
· Make It a CHORUS: Context- and Knowledge-aware Item Modeling for Recommendation
· Investigating reading behavior in Fine-grained Relevance Judgment
· An analysis of BERT in document ranking
· Cascade or Recency: Constructing Better Evaluation Metrics for Session Search
· Beyond User Embedding Matrix: Learning to Hash for Modeling Large-Scale Users in Recommendation
· Preference-based Evaluation Metrics for Web Image Search
· Models Versus Satisfaction: Towards a Better Understanding of Evaluation Metrics
· Influence Function for Unbiased Recommendation
· Neighbor Interaction Aware Graph Convolution Networks for Recommendation
· A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data
· Multi-Branch Convolutional Network for Context-Aware Recommendation
· Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach
· JIT$^2$R:A Joint Framework for Item Tagging and Tag-based Recommendation
· AutoGroup: Automatic Feature Grouping for Modelling Explicit High-Order Feature Interactions in CTR Prediction
马少平
入选论文
· Investigating reading behavior in Fine-grained Relevance Judgment
· An analysis of BERT in document ranking
· Make It a CHORUS: Context- and Knowledge-aware Item Modeling for Recommendation
· Cascade or Recency: Constructing Better Evaluation Metrics for Session Search
· Beyond User Embedding Matrix: Learning to Hash for Modeling Large-Scale Users in Recommendation
· Preference-based Evaluation Metrics for Web Image Search
· Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach
· Try This Instead: Personalized and Interpretable Substitute Recommendation
· How to Retrain a Recommender System
· Lightening Graph Convolution Network for Recommendation
Tree-augmented Cross-Modal Encoding for Complex-Query Video Retrieval
文继荣
共有6篇论文入选
毕业于中国人民大学信息学院计算机科学与技术专业，获得工学学士和硕士学位。1999年于中科院计算所获得博士学位，同年加入微软亚洲研究院，自2008年起担任高级研究员和互联网搜索与数据挖掘组主任。在微软亚洲研究院工作的14年中，获得50多项美国专利，其中一些成果已经被用于重要的微软产品中(如微软搜索引擎Bing)。所领导的研究团队开发出了微软学术搜索(http://academic.research.microsoft.com)、人立方(http://renlifang.msra.cn/)、产品搜索等有影响力的互联网应用。在国际著名会议和期刊上发表了一百多篇论文，担任过许多国际会议和研讨会的程序委员和主席。目前是信息检索领域主要期刊ACM Transactions on Information Systems(TOIS)的副主编。
入选论文
· SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval
· Sequential Recommendation with Self-Attentive Multi-Adversarial Network
· DVGAN: A Minimax Game for Search Result Diversification Combining Explicit and Implicit Features
· Encoding History with Context-aware Representation Learning for Personalized Search
· Reinforcement Learning to Rank with Pairwise Policy Gradient
· Employing Personal Word Embeddings for Personalized Search
此次会议中“后浪”们也有着精彩的表现！
共有55名同学有至少一篇的论文。其中，以下同学各有两篇一作论文入选：卡内基梅隆大学计算机科学学院语言技术研究所的博士生Zhuyun Dai、罗格斯大学计算机专业的葛英强(Yingqiang Ge)、马萨诸塞大学阿默斯特分校信息与计算机科学学院的博士生Chen Qu、清华大学计算机科学与技术系博士生张帆(Fan Zhang)、德州农工大学计算机科学与工程系的博士生Ziwei Zhu、武汉大学信息检索与知识挖掘研究所的博士生贺国秀(Guoxiu He)， 和伊利诺伊大学香槟分校计算机科学系的博士生庄弘磊(Honglei Zhuang)。
看了关于SIGIR 2020 上华人学者的介绍，你决定pick谁了吗？快去加油助威吧！
想要查看更多学者的详细信息，可以移步 AMiner 会议智图开放平台 SIGIR 2020 专题全析图（https://www.aminer.cn/conf/sigir2020/homepage），其内容包括论文、作者、华人学者、一作华人学生、论文 PPT 和视频等多维分析服务，是参会学者的会议智能助理。