wsdm_21.md

RecSys-Papers-from-WSDM 2021

Reinforcement Learning

622: User Response Models to Improve a REINFORCE Recommender System

Minmin Chen, Bo Chang, Can Xu, Ed Chi (Google)

Citations 26

Keywords Reinforcement learning; Long-term user engagement; Recommender system

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512: Towards Long-term Fairness in Recommendation

Yingqiang Ge (Rutgers University), Shuchang Liu (Rutgers University), Ruoyuan Gao (Rutgers University), Yikun Xian (Rutgers University), Yunqi Li (Rutgers University), Xiangyu Zhao (Michigan State University), Changhua Pei (Tsinghua University), Fei Sun (Alibaba Group), Junfeng Ge (Alibaba Group), Wenwu Ou (alibaba group), Yongfeng Zhang (Rutgers University)

Keywords Recommender System; Long-term Fairness; Reinforcement Learning; Constrained Policy Optimization; Unbiased Recommendation

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Session Based & Sequential Recommendations

74: Sparse-Interest Network for Sequential Recommendation

Qiaoyu Tan (Texas A&M University), Jianwei Zhang (Alibaba Group), Jiangchao Yao (Alibaba Group), Ninghao Liu (Texas A&M University), Jingren Zhou (Alibaba Group), Hongxia Yang (Alibaba Group), Xia Hu (Texas A&M University)

Citations 1

Keywords Recommender system, Sequential recommendation, Sparse-interest network, Multi-interest extraction

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441: An Efficient and Effective Framework for Session-based Social Recommendation

Tianwen Chen, Raymond Chi-Wing Wong (The Hong Kong University of Science and Technology)

Keywords session-based recommendation, social recommendation, social network, graph neural network

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294: Origin-Aware Next Destination Recommendation with Personalized Preference Attention

Xiang Hui Nicholas Lim (Grab), Kuen Yew Bryan Hooi (NUS), See Kiong Ng (NUS), Xueou Wang (NUS), Yong Liang Goh (Grab), Renrong Weng (Grab), Rui Tan (Grab)

Keywords Recommender System; Recurrent Neural Network; Spatio-Temporal

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246: Real-time Relevant Recommendation Suggestion?

Ruobing Xie, Rui Wang, Shaoliang Zhang, Zhihong Yang, Feng Xia, Leyu Lin (WeChat Search Application Department, Tencent)

Keywords recommendation suggestion; recommender system; relevant recommendation ACM Reference Fo

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Bias & Unbiased

508: Popularity-Opportunity Bias in Collaborative Filtering

Ziwei Zhu, Yun He, Xing Zhao, Yin Zhang, Jianling Wang, James Caverlee (Texas A&M University)

Citations 1

Keywords recommender systems; statistical parity; equal opportunity; recommendation bias

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132: Combating Selection Biases in Recommender Systems with A Few Unbiased Ratings

Xiaojie Wang (Amazon.com Inc.), Rui Zhang (University of Melbourne), Yu Sun (Twitter Inc.), Jianzhong Qi (University of Melbourne)

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51: Unbiased Learning to Rank in Feeds Recommendation

Xinwei Wu (Jilin University), Hechang Chen (Jilin University), Jiashu Zhao (Wilfrid Laurier University), Li He (JD.COM), Dawei Yin (baidu.com), Yi Chang (Jilin University)

Keywords Feeds Recommendation; Learning to Rank; Unbiased Learning

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Application

330: Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems

Xuezhi Wang (Google), Nithum Thain (Jigsaw), Anu Sinha (Google), Flavien Prost (Google), Ed H. Chi (Google), Jilin Chen (Google), Alex Beutel (Google)

Citations 2

Keywords compositional fairness; recommender systems; ranking fairness

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634: Leave No User Behind: Towards Improving the Utility of Recommender Systems for Non-mainstream Users

Roger Zhe Li, Julián Urbano, Alan Hanjalic (Delft University of Technology)

Citations 1

Keywords Recommender Systems; Mainstream Bias; User Fairness

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494: Explainable Recommendation with Comparative Constraints on Product Aspects

Trung-Hoang Le, Hady Lauw (Singapore Management University)

Keywords Explainable Recommendation; Comparative Constraints

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Interesting

133: Denoising Implicit Feedback for Recommendation

Wenjie Wang (National University of Singapore), Fuli Feng (National University of Singapore), Xiangnan He (University of Science and Technology of China), Liqiang Nie (Shandong University), Tat-Seng Chua (National University of Singapore)

Citations 4

Keywords Recommender System, False-positive Feedback, Adaptive Denoising Training

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609: A Black-Box Attack Model for Visually-Aware Recommenders

Rami Cohen (Intuit), Oren Sar Shalom (Bar Ilan University), Dietmar Jannach (University of Klagenfurt), Amihood Amir (Bar-Ilan University and Johns Hopkins University)

Citations 1

Keywords Recommender Systems, Attacks, Adversarial Examples

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155: Diverse User Preference Elicitation with Multi-Armed Bandits

Javier Parapar, Filip Radlinski (Google)

Keywords recommender systems, preference elicitation, diversity, bandits

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101: Adapting User Preference to Online Feedback in Multi-round Conversational Recommendation

Kerui Xu (Beijing University of Posts and Telecommunications), Jingxuan Yang (Beijing University of Posts and Telecommunications), Jun Xu (Gaoling School of Artificial Intelligence, Renmin University of China), Sheng Gao (Beijing University of Posts and Telecommunications), Jun Guo (Beijing University of Posts and Telecommunications), Ji-Rong Wen (Gaoling School of Artificial Intelligence, Renmin University of China)

Keywords Multi-round conversational recommendation; User preference

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Scalability

495: Personalized Food Recommendation as Constrained Question Answering over a Large-scale Food Knowledge Graph

Yu Chen (RPI), Ananya Subburathinam (RPI), Ching-Hua Chen (IBM), Mohammed J. Zaki (RPI)

Keywords food recommendation, personal health, healthy diet, constrained question answering, knowledge graphs

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107: Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems

Zhe Chen, Yuyan Wang, Dong Lin, Zhiyuan Cheng, Lichan Hong, Ed Chi, Claire Cui (GOOGLE)

Keywords Ensemble, Neural Networks, Neuron Activation, Prediction Uncertainty, Recommender Systems

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Posters

219: Decomposed Collaborative Filtering: Modeling Explicit and Implicit Factors For Recommender Systems

Hao Chen (Shanghai Jiao Tong University), Xin Xin (University of Glasgow), Dong Wang (Shanghai Jiao Tong University), Yue Ding (Shanghai Jiao Tong University)

Keywords Recommender systems, Graph neural networks, Knowledge Graph

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84: Alleviating Cold-Start Problems in Recommendation through Pseudo-Labelling over Knowledge Graph

Riku Togashi (CyberAgent, Inc.), Mayu Otani (CyberAgent, Inc.), Shin'Ichi Satoh (National Institute of Informatics)

Keywords knowledge graph; cold-start recommendation; knowledge-aware re commendation; graph neural networks; semi-supervised learning

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231: Learning User Representations with Hypercuboids for Recommender Systems

Shuai Zhang (ETH Zurich), Huoyu Liu (Alibaba), Aston Zhang (UIUC), Yue Hu (Alibaba), Ce Zhang (ETH Zurich), Yumeng Li (Alibaba), Tanchao Zhu (Alibaba), Shaojian He (Alibaba), Wenwu Ou (Alibaba)

Keywords Recommender Systems, Hypercuboids, User Representation

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433: Enhancing Neural Recommender Models through Domain-Specific Concordance

Ananth Balashankar (New York University), Alex Beutel (Google), Lakshminarayanan Subramanian (New York University)

Keywords Recommender Systems, Hypercuboids, User Representation

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541: Explanation as a Defense of Recommendation

Aobo Yang (University of Virginia), Nan Wang (University of Virginia), Hongbo Deng (Alibaba Group), Hongning Wang (University of Virginia)

Keywords Explainable Recommendation, Natural Language Generation, Sentiment Alignment

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558: Heterogeneous Graph Augmented Multi-Scenario Sharing Recommendation with Tree-Guided Expert Networks

Xichuan Niu (Wuhan University), Bofang Li (Alibaba Group), Chenliang Li (Wuhan University), Jun Tan (Alibaba Group), Rong Xiao (Alibaba Group), Hongbo Deng (Alibaba Group)

Keywords Heterogeneous Graph, E-Commerce, Sharing Recommendation

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614: Temporal Meta-path Guided Explainable Recommendation

Hongxu Chen (University of Technology Sydney), Yicong Li (University of Technology Sydney), Xiangguo Sun (Southeast University), Guandong Xu (University of Technology Sydney), Hongzhi Yin (The University of Queensland)

Keywords explainable recommendation, temporal recommendation

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