Papers related to the Recommender System from SIGIR 2021 (including the links for Paper PDF, Github Code and Dataset)
- L: Long Papers
- S: Short Papers
- R: Resource Papers
L14, L28, L42
L3, L5, L32, L35, L43, S2, S6, S9, S15, S20
L6, L11, L25, S3, S22
L5, L7, L12, L28, L31, L33, L37, L39, L42, S19, S22, R3
L13, L30, S14, R4
L12, L27, L41, R3
L24, L31, S5, S17, S21
S12, S19
L22, L40, S23
L12, L16, L41, S11
L1, L36, S8
L6, L15, S3, S5, S9
L37, L25
L29, L33, L47, L48, S11, S15, S23
L20, L39
L8, L19, L21, L38, L45, L48, S4, S7
[L1] A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images [PDF]
Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta and Felice Antonio Merra
[L2] On Interpretation and Measurement of Soft Attributes for Recommendation [PDF]
Krisztian Balog, Filip Radlinski and Alexandros Karatzoglou
[L3] Category-aware Collaborative Sequential Recommendation
Renqin Cai, Hongning Wang, Jibang Wu, Chong Wang and Aidan San
[L4] DEKR: Description Enhanced Knowledge Graph for Machine Learning Method Recommendation
Xianshuai Cao, Yuliang Shi, Han Yu, Jihu Wang, Xinjun Wang, Zhongmin Yan and Zhiyong Chen
[L5] Sequential Recommendation with Graph Convolutional Networks
Jianxin Chang, Chen Gao, Yu Zheng, Yiqun Hui, Yanan Niu, Yang Song, Depeng Jin and Yong Li
[L6] Dual Attention Transfer in Session-based Recommendation with Multi Dimensional Integration
Chen Chen, Jie Guo and Bin Song
[L7] Structured Graph Convolutional Networks with Stochastic Masks for Recommender Systems
Huiyuan Chen, Lan Wang, Yusan Lin, Michael Yeh, Fei Wang and Hao Yang
[L8] AutoDebias: Learning to Debias for Recommendation [PDF] [CODE]
Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin and Keping Yang
[L9] Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation [PDF]
Lei Chen, Le Wu, Kun Zhang, Richang Hong and Meng Wang
[L10] Learning Recommender Systems with Implicit Feedback via Soft Target Enhancement
Mingyue Cheng, Fajie Yuan, Qi Liu, Shenyang Ge, Zhi Li, Runlong Yu, Defu Lian, Senchao Yuan and Enhong Chen
[L11] Unsupervised Proxy Selection for Session-based Recommender Systems
Junsu Cho, Seongku Kang, Dongmin Hyun and Hwanjo Yu
[L12] Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning [PDF]
Yang Deng, Yaliang Li, Fei Sun, Bolin Ding and Wai Lam
[L13] ReXPlug: Explainable Recommendation using Plug-and-Play Language Model
Deepesh Hada, Vijaikumar M and Shirish Shevade
[L14] Bootstrapping User and Item Representations for One-Class Collaborative Filtering [PDF]
Dongha Lee, Seongku Kang, Hyunjun Ju, Chanyoung Park and Hwanjo Yu
[L15] Package Recommendation with Intra- and Inter-Package Attention Networks [PDF]
Chen Li, Yuanfu Lu, Wei Wang, Chuan Shi, Ruobing Xie, Haili Yang, Cheng Yang, Xu Zhang and Leyu Lin
[L16] When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution [PDF]
Chuanhao Li, Qingyun Wu and Hongning Wang
[L17] Path-based Deep Network for Candidate Item Matching in Recommenders [PDF]
Houyi Li, Zhihong Chen, Chenliang Li, Rong Xiao, Hongbo Deng, Peng Zhang, Yongchao Liu and Haihong Tang
[L18] New Insights into Metric Optimization for Ranking-based Recommendation [PDF] [CODE]
Roger Zhe Li, Julián Urbano and Alan Hanjalic
[L19] Personalized Counterfactual Fairness in Recommendation
Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge and Yongfeng Zhang
[L20] Enhancing Domain-Level and User-Level Adaptivity in Diversified Recommendation
Yile Liang, Tieyun Qian, Qing Li and Hongzhi Yin
[L21] Mitigating Sentiment Bias for Recommender Systems
Chen Lin, Xinyi Liu, Guipeng Xv and Hui Li
[L22] Federated Collaborative Transfer for Cross-Domain Recommendation
Shuchang Liu, Shuyuan Xu, Wenhui Yu, Zuohui Fu, Yongfeng Zhang and Amelie Marian
[L23] Standing in Your Shoes: External Assessments for Personalized Recommender Systems [PDF]
Hongyu Lu, Weizhi Ma, Min Zhang, Maarten de Rijke, Yiqun Liu and Shaoping Ma
[L24] Personalized News Recommendation with Knowledge-aware News Interactions [PDF]
Tao Qi, Fangzhao Wu, Chuhan Wu and Yongfeng Huang
[L25] The World is Binary: Contrastive Learning for Denoising Next Basket Recommendation [CODE]
Yuqi Qin, Pengfei Wang and Chenliang Li
[L26] A Guided Learning Approach for Item Recommendation via Surrogate Loss Learning
Ahmed Rashed, Lars Schmidt-Thieme and Josif Grabocka
[L27] Learning to Ask Appropriate Questions in Conversational Recommendation
Xuhui Ren, Hongzhi Yin, Tong Chen, Hao Wang, Zi Huang and Kai Zheng
[L28] Neural Graph Matching based Collaborative Filtering [PDF] [CODE]
Yixin Su, Rui Zhang, Sarah M. Erfani and Junhao Gan
[L29] FORM: Follow the Online Regularized Meta-Leader for Cold-Start Recommendation
Xuehan Sun, Tianyao Shi, Xiaofeng Gao, Yanrong Kang and Guihai Chen
[L30] User-Centric Path Reasoning towards Explainable Recommendation
Chang-You Tai, Huang Liangying, Chienkun Huang and Ku Lun-Wei
[L31] Joint Knowledge Pruning and Recurrent Graph Convolution for News Recommendation [PDF]
Yu Tian, Yuhao Yang, Xudong Ren, Pengfei Wang, Fangzhao Wu, Qian Wang and Chenliang Li
[L32] StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking [PDF] [CODE]
Jiachun Wang, Fajie Yuan, Jian Chen, Qingyao Wu, Min Yang, Yang Sun and Guoxiao Zhang
[L33] Privileged Graph Distillation for Cold-start Recommendation [PDF]
Shuai Wang, Kun Zhang, Le Wu, Haiping Ma, Richang Hong and Meng Wang
[L34] Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue [PDF]
Wenjie Wang, Fuli Feng, Xiangnan He, Hanwang Zhang and Tat-Seng Chua
[L35] Counterfactual Data-Augmented Sequential Recommendation
Zhenlei Wang, Jingsen Zhang, Hongteng Xu, Xu Chen, Yongfeng Zhang, Wayne Xin Zhao and Ji-Rong Wen
[L36] Fight Fire with Fire: Towards Robust Recommender Systems via Adversarial Poisoning Training
Chenwang Wu, Defu Lian, Yong Ge, Zhihao Zhu, Enhong Chen and Senchao Yuan
[L37] Self-supervised Graph Learning for Recommendation [PDF] [CODE]
Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian and Xing Xie
[L38] TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers [PDF]
Yao Wu, Jian Cao, Guandong Xu and Yudong Tan
[L39] Graph Meta Network for Multi-Behavior Recommendation with Interaction Heterogeneity and Diversity
Lianghao Xia, Chao Huang, Yong Xu, Peng Dai and Liefeng Bo
[L40] Learning Domain Semantics and Cross-Domain Correlations for Paper Recommendation [PDF]
Yi Xie, Yuqing Sun and Elisa Bertino
[L41] Comparison-based Conversational Recommender System with Relative Bandit Feedback
Zhihui Xie, Tong Yu, Canzhe Zhao and Shuai Li
[L42] Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization
Yonghui Yang, Le Wu, Richang Hong, Kun Zhang and Meng Wang
[L43] CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation
Shengyu Zhang, Dong Yao, Zhou Zhao, Tat-Seng Chua and Fei Wu
[L44] Counterfactual Reward Modification for Streaming Recommendation with Delayed Feedback
Xiao Zhang, Haonan Jia, Hanjing Su, Wenhan Wang, Jun Xu and Ji-Rong Wen
[L45] Causal Intervention for Leveraging Popularity Bias in Recommendation [PDF] [CODE]
Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling and Yongdong Zhang
[L46] UGRec: Modeling Directed and Undirected Relations for Recommendation [PDF]
Xinxiao Zhao, Zhiyong Cheng, Lei Zhu, Jiecai Zheng and Xueqing Li
[L47] Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks [PDF]
Yongchun Zhu, Ruobing Xie, Fuzhen Zhuang, Kaikai Ge, Ying Sun, Xu Zhang, Leyu Lin and Juan Cao
[L48] Fairness among New Items in Cold Start Recommender Systems [PDF]
Ziwei Zhu, Jingu Kim, Trung Nguyen, Aish Fenton and James Caverlee
[S1] Variational Autoencoders for Top-K Recommendation with Implicit Feedback
Bahare Askari, Jaroslaw Szlichta and Amirali Salehi-Abari
[S2] Motif-aware Sequential Recommendation
Zeyu Cui, Yinjiang Cai, Shu Wu, Xibo Ma and Liang Wang
[S3] Lighter and Better: Low-Rank Decomposed Self-Attention Networks for Next-Item Recommendation [PDF]
Xinyan Fan, Zheng Liu, Jianxun Lian, Wayne Xin Zhao, Xing Xie and Ji-Rong Wen
[S4] The Winner Takes it All: Geographic Imbalance and Provider (Un)fairness in Educational Recommender Systems
Elizabeth Gómez, Carlos Shui Zhang, Ludovico Boratto, Maria Salamo and Mirko Marras
[S5] RMBERT:News Recommendation via Recurrent Reasoning Memory Network over BERT
Qinglin Jia, Jingjie Li, Qi Zhang, Xiuqiang He and Jieming Zhu
[S6] Entangled Bidirectional Encoder to Autoregressive Decoder for Sequential Recommendation
Taegwan Kang, Hwanhee Lee, Byeongjin Choe and Kyomin Jung
[S7] Dual Unbiased Recommender Learning for Implicit Feedback
Jae-woong Lee, Seongmin Park and Jongwuk Lee
[S8] Info-flow Enhanced GANs for Recommender
Yuan Lin, Zhang Xie, Bo Xu, Kan Xu and Hongfei Lin
[S9] Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer [PDF] [CODE]
Zhiwei Liu, Ziwei Fan, Yu Wang and Philip S. Yu
[S10] Neural Representations in Hybrid Recommender Systems: Prediction versus Regularization [PDF]
Ramin Raziperchikolaei, Tianyu Li and Young-joo Chung
[S11] Cluster-Based Bandits: Fast Cold-Start for Recommender System New Users [PDF]
Sulthana Shams, Daron Anderson and Douglas Leith
[S12] Social Recommendation with Implicit Social Influence
Changhao Song, Bo Wang, Qinxue Jiang, Ruifang He and Yuexian Hou
[S13] Underestimation Refinement: A General Enhancement Strategy for Exploration in Recommendation Systems
Yuhai Song, Lu Wang, Haoming Dang, Weiwei Zhou, Jing Guan, Xiwei Zhao, Changping Peng, Yongjun Bao and Jingping Shao
[S14] Counterfactual Explanations for Neural Recommenders [PDF] [CODE]
Khanh Hiep Tran, Azin Ghazimatin and Rishiraj Saha Roy
[S15] Sequential Recommendation for Cold-start Users with Meta Transitional Learning [PDF]
Jianling Wang, Kaize Ding and James Caverlee
[S16] Cross-Batch Negative Sampling for Training Two-Tower Recommenders
Jinpeng Wang, Jieming Zhu and Xiuqiang He
[S17] Empowering News Recommendation with Pre-trained Language Models [PDF]
Chuhan Wu, Fangzhao Wu, Tao Qi and Yongfeng Huang
[S18] Bayesian Critiquing with Keyphrase Activation Vectors for VAE-based Recommender Systems [PDF]
Hojin Yang, Tianshu Shen and Scott Sanner
[S19] ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation [PDF] [CODE]
Liangwei Yang, Zhiwei Liu, Yingtong Dou, Jing Ma and Philip S. Yu
[S20] ICAI-SR: Item Categorical Attribute Integrated Sequential Recommendation
Xu Yuan, Dongsheng Duan, Lingling Tong, Lei Shi and Cheng Zhang
[S21] AMM: Attentive Multi-field Matching for News Recommendation
Qi Zhang, Qinglin Jia, Chuyuan Wang, Jingjie Li, Zhaowei Wang and Xiuqiang He
[S22] Temporal Augmented Graph Neural Networks for Session-Based Recommendations
Huachi Zhou, Qiaoyu Tan, Xiao Huang, Kaixiong Zhou and Xiaoling Wang
[S23] Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users [PDF]
Yongchun Zhu, Kaikai Ge, Fuzhen Zhuang, Ruobing Xie, Dongbo Xi, Xu Zhang, Leyu Lin and Qing He
[R1] POINTREC: A Test Collection for Narrative-driven Point of Interest Recommendation [PDF] [CODE]
Jafar Afzali, Aleksander Mark Drzewiecki and Krisztian Balog
[R2] Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation [PDF] [CODE]
Vito Walter Anelli, Alejandro Bellogin, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco Maria Donini and Tommaso Di Noia
[R3] HOOPS: Human-in-the-Loop Graph Reasoning for Conversational Recommendation [PDF] [CODE] [DATASET]
Zuohui Fu, Yikun Xian, Yaxin Zhu, Shuyuan Xu, Zelong Li, Gerard de Melo and Yongfeng Zhang
[R4] EXTRA: Explanation Ranking Datasets for Explainable Recommendation [PDF] [CODE] [DATASET]
Lei Li, Yongfeng Zhang and Li Chen