WWW 2023组委会近日放出了正式接收论文清单。大会共收到了1900篇论文，接收365篇，录用率为19.2%。完整清单见：
www2023.thewebconf.org/program/accepted-papers/
近几年，推荐系统一直是WWW会议上热门主题，其中365篇接收论文中大约70多篇推荐系统相关论文，其广泛受到了学术界和业界的关注。部分pdf版本可在以下链接查看：
https://github.com/hongleizhang/RSPapers/tree/master/00-Latest_Papers/WWW2023
本文整理了WWW2023上推荐系统方向的论文，共计72篇。其中主题主要涉及时序推荐、基于图的推荐、可解释推荐、推荐系统中的bias、因果相关、公平性和隐私保护、强化学习、冷启动、跨领域、多任务、对比学习、多模态等。
1. Submodular Maximization in the Presence of Biases with Applications to Recommendation
Anay Mehrotra and Nisheeth K. Vishnoi
2. Scoping Fairness Objectives and Identifying Fairness Metrics for Recommender Systems: The Practitioners’ Perspective
Jessie J. Smith, Lex Beattie and Henriette Cramer
3. P-MMF: Provider Max-min Fairness Re-ranking in Recommender System
Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang and Zhenhua Dong
4. Fairly Adaptive Negative Sampling for Recommendations
Xiao Chen, Wenqi Fan, Jingfan Chen, Haochen Liu, Zitao Liu, Qing Li and Zhaoxiang Zhang
5. RL-MPCA: A Reinforcement Learning Based Multi-Phase Computation Allocation Approach for Recommender Systems
Jiahong Zhou, Shunhui Mao, Guoliang Yang, Bo Tang, Qianlong Xie, Lebin Lin, Xingxing Wang and Dong Wang
6. Collaboration-Aware Graph Convolutional Network for Recommender Systems
Yu Wang, Yuying Zhao, Yi Zhang and Tyler Derr
7. Enhancing Hierarchy-Aware Graph Networks with Deep Dual Clustering for Session-based Recommendation
Jiajie Su, Xiaolin Zheng, Weiming Liu, Fei Wu, Chaochao Chen and Haoming Lyu
8. ConsRec: Learning Consensus Behind Interactions for Group Recommendation
Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang, Yangyong Zhu and Philip Yu
9. Semi-decentralized Federated Ego Graph Learning for Recommendation
Liang Qu, Ningzhi Tang, Ruiqi Zheng, Quoc Viet Hung Nguyen, Zi Huang, Yuhui Shi and Hongzhi Yin
10. Joint Internal Multi-Interest Exploration and External Domain Alignment for Cross Domain Sequential Recommendation
Weiming Liu, Xiaolin Zheng, Chaochao Chen, Jiajie Su, Xinting Liao, Mengling Hu and Yanchao Tan
11. Intra and Inter Domain HyperGraph Convolutional Network for Cross-Domain Recommendation
Zhongxuan Han, Xiaolin Zheng, Chaochao Chen, Wenjie Cheng and Yang Yao
12. Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation
Di Jin, Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin and Shirui Pan
13. ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation
Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov and Jie Tang
14. Enhancing User Personalization in Conversational Recommenders
Allen Lin, Ziwei Zhu, Jianling Wang and James Caverlee
15. LINet: A Location and Intention-Aware Neural Network for Hotel Group Recommendation
Ruitao Zhu, Detao Lv, Yao Yu, Ruihao Zhu, Zhenzhe Zheng, Ke Bu, Quan Lu and Fan Wu
16. Multi-Modal Adversarial Self-Supervised Learning for Recommendation
Wei Wei, Chao Huang, Lianghao Xia and Chuxu Zhang
17. Distillation from Heterogeneous Models for Top-K Recommendation
Seongku Kang, Wonbin Kweon, Dongha Lee, Jianxun Lian, Xing Xie and Hwanjo Yu
18. On the Theories Behind Hard Negative Sampling for Recommendation
Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao and Xiangnan He
19. Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation
Tianjun Wei, Jianghong Ma and Tommy W. S. Chow
20. Exploration and Regularization of the Latent Action Space in Recommendation
Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Dong Zheng, Peng Jiang, Kun Gai, Ji Jiang, Xiangyu Zhao and Yongfeng Zhang
21. Bootstrap Latent Representations for Multi-modal Recommendation
Xin Zhou, Hongyu Zhou, Yong Liu, Zhiwei Zeng, Chunyan Miao, Pengwei Wang, Yuan You and Feijun Jiang
22. Two-Stage Constrained Actor-Critic for Short Video Recommendation
Qingpeng Cai, Zhenghai Xue, Chi Zhang, Wanqi Xue, Shuchang Liu, Ruohan Zhan, Xueliang Wang, Tianyou Zuo, Wentao Xie, Dong Zheng, Peng Jiang and Kun Gai
23. Recommendation with Causality enhanced Natural Language Explanations
Jingsen Zhang, Xu Chen, Jiakai Tang, Weiqi Shao, Quanyu Dai, Zhenhua Dong and Rui Zhang
24. Cross-domain recommendation via user interest alignment
Chuang Zhao, Hongke Zhao, Ming He, Jian Zhang and Jianping Fan
25. A Simple Data-Augmented Framework For Smoothed Recommender System
Zhenlei Wang and Xu Chen
26. Dual-interest Factorization-heads Attention for Sequential Recommendation
Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Zhiheng Li, Depeng Jin and Yong Li
27. Contrastive Collaborative Filtering for Cold-Start Item Recommendation
Zhihui Zhou, Lilin Zhang and Ning Yang
28. Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model
Xiaoyu You, Chi Lee, Daizong Ding, Mi Zhang, Fuli Feng, Xudong Pan and Min Yang
29. Compressed Interaction Graph based Framework for Multi-behavior Recommendation
Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li and Rui Zhang
30. A Counterfactual Collaborative Session-based Recommender System
Wenzhuo Song, Shoujin Wang, Yan Wang, Kunpeng Liu, Xueyan Liu and Minghao Yin
31. Correlative Preference Transfer with Hierarchical Hypergraph Network for Multi-Domain Recommendation
Zixuan Xu, Penghui Wei, Shaoguo Liu, Weimin Zhang, Liang Wang and Bo Zheng
32. Automated Self-Supervised Learning for Recommendation with Masked Graph Transformer
Lianghao Xia, Chao Huang, Chunzhen Huang, Kangyi Lin, Tao Yu and Ben Kao
33. Improving Recommendation Fairness via Data Augmentation
Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou and Meng Wang
34. ColdNAS: Search to Modulate for User Cold-Start Recommendation
Shiguang Wu, Yaqing Wang, Qinghe Jing, Daxiang Dong, Quanming Yao and Dejing Dou
35. AutoS2AE: Automate to Regularize Sparse Shallow Autoencoders for Recommendation
Rui Fan, Jin Chen, Yuanhao Pu, Zhihao Zhu, Defu Lian and Enhong Chen
36. Quantize Sequential Recommenders Without Private Data
Lingfeng Shi, Yuang Liu, Jun Wang and Wei Zhang
37. Interaction-level Membership Inference Attack Against Federated Recommender Systems
Wei Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Lizhen Cui, Tieke He and Hongzhi Yin
38. Contrastive Learning with Interest and Conformity Disentanglement for Sequential Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang, Da Luo and Kangyi Lin
39. Clustered Embedding Learning for Large-scale Recommender Systems
Yizhou Chen, Guangda Huzhang, Qingtao Yu, Hui Sun, Heng-Yi Li, Jingyi Li, Yabo Ni, Anxiang Zeng, Han Yu and Zhiming Zhou
40. Adap-: Adpatively Modulating Embedding Magnitude for Recommendation
Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou and Xiangnan He
41. Robust Preference-Guided Denoising for Graph based Social Recommendation
Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin and Yong Li
42. MMMLP: Multi-modal Multilayer Perceptron for sequence recommendation
Jiahao Liang, Xiangyu Zhao, Muyang Li, Zijian Zhang, Haochen Liu and Liu Zitao
43. Response-act Guided Reinforced Dialogue Generation for Mental Health Counseling
Aseem Srivastava, Ishan Pandey, Md Shad Akhtar and Tanmoy Chakraborty
44. Few-shot News Recommendation via Cross-lingual Transfer
Taicheng Guo, Lu Yu, Basem Shihada and Xiangliang Zhang
45. User Retention-oriented Recommendation with Decision Transformer
Kesen Zhao, Lixin Zou, Xiangyu Zhao, Maolin Wang and Dawei Yin
46. Cooperative Retriever and Ranker in Deep Recommenders
Xu Huang, Defu Lian, Jin Chen, Liu Zheng, Xing Xie and Enhong Chen
47. Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders
Yupeng Hou, Zhankui He, Julian McAuley and Wayne Xin Zhao
48. Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders
Yupeng Hou, Zhankui He, Julian McAuley and Wayne Xin Zhao
49. Show Me The Best Outfit for A Certain Scene: A Scene-aware Fashion Recommender System
Tangwei Ye, Liang Hu, Qi Zhang, Zhong Yuan Lai, Usman Naseem and Dora D. Liu
50. Multi-Behavior Recommendation with Cascading Graph Convolutional Network
Zhiyong Cheng, Sai Han, Fan Liu, Lei Zhu, Zan Gao and Yuxin Peng
51. AutoMLP: Automated MLP for Sequential Recommendations
Muyang Li, Zijian Zhang, Xiangyu Zhao, Minghao Zhao, Runze Wu and Ruocheng Guo
52. NASRec: Weight Sharing Neural Architecture Search for Recommender Systems
Tunhou Zhang, Dehua Cheng, Yuchen He, Zhengxing Chen, Xiaoliang Dai, Liang Xiong, Feng Yan, Hai Li, Yiran Chen and Wei Wen
53. Membership Inference Attacks Against Sequential Recommender Systems
Zhihao Zhu, Chenwang Wu, Rui Fan, Defu Lian and Enhong Chen
54. Communicative MARL-based Relevance Discerning Network for Repetition-Aware Recommendation
Kaiyuan Li, Pengfei Wang, Haitao Wang, Qiang Liu, Xingxing Wang, Dong Wang and Shangguang Wang
55. Invariant Collaborative Filtering to Popularity Distribution Shift
An Zhang, Jingnan Zheng, Xiang Wang, Yancheng Yuan and Tat-Seng Chua
56. Modeling Temporal Positive and Negative Excitation for Sequential Recommendation
Chengkai Huang, Shoujin Wang, Xianzhi Wang and Lina Yao
57. Personalized Graph Signal Processing for Collaborative Filtering
Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang and Ning Gu
58. Multi-Task Recommendations with Reinforcement Learning
Ziru Liu, Jiejie Tian, Qingpeng Cai, Xiangyu Zhao, Jingtong Gao, Shuchang Liu, Dayou Chen, Tonghao He, Dong Zheng, Peng Jiang and Kun Gai
59. A Self-Correcting Sequential Recommender
Yujie Lin, Chenyang Wang, Zhumin Chen, Zhaochun Ren, Xin Xin, Qiang Yan, Maarten de Rijke, Xiuzhen Cheng and Pengjie Ren
60. Cross-domain Recommendation with Behavioral Importance Perception
Hong Chen, Xin Wang, Ruobing Xie, Yuwei Zhou and Wenwu Zhu
61. Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations
Haoxuan Li, Yanghao Xiao, Chunyuan Zheng and Peng Wu
62. Code Recommendation for Open Source Software Developers
Yiqiao Jin, Yunsheng Bai, Yanqiao Zhu, Yizhou Sun and Wei Wang
63. Denoising and Prompt-Tuning for Multi-Behavior Recommendation
Chi Zhang, Xiangyu Zhao, Rui Chen, Qilong Han and Li Li
64. Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation
Ziwei Fan, Zhiwei Liu, Hao Peng and Philip S Yu
65. Confident Action Decision via Hierarchical Policy Learning for Conversational Recommendation
Heeseon Kim, Hyeongjun Yang and Kyong-Ho Lee
66. CAMUS: Attribute-Aware Counterfactual Augmentation for Minority Users in Recommendation
Yuxin Ying, Fuzhen Zhuang, Yongchun Zhu, Deqing Wang and Hongwei Zheng
67. Dynamically Expandable Graph Convolution for Streaming Recommendation
Bowei He, Xu He, Yingxue Zhang, Ruiming Tang and Chen Ma
68. Dual Policy Learning for Aggregation Optimization in Recommender Systems
Heesoo Jung, Hogun Park and Sangpil Kim
69. Automatic Feature Selection By One-Shot Neural Architecture Search In Recommendation Systems
Haiyang Wu, He Wei, Yuekui Yang, Yangyang Tang, Meixi Liu and Jianfeng Li
70. Semi-supervised Adversarial Learning for Complementary Item Recommendation
Koby Bibas, Oren Sar Shalom and Dietmar Jannach
71. Towards Explainable Collaborative Filtering with Taste Clusters Learning
Yuntao Du, Jianxun Lian, Jing Yao, Xiting Wang, Mingqi Wu, Lu Chen, Yunjun Gao and Xing Xie
72. Towards Explainable Collaborative Filtering with Taste Clusters Learning
Yuntao Du, Jianxun Lian, Jing Yao, Xiting Wang, Mingqi Wu, Lu Chen, Yunjun Gao and Xing Xie
