WWW2023推荐系统论文集锦，推荐系统方向占比高达72/365

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