PaperNotes

不断更新阅读的论文，简单记录一下

21.10

• Gao, Chen, Yu Zheng, Nian Li, Yinfeng Li, Yingrong Qin, Jinghua Piao, Yuhan Quan, et al. “Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions.” ArXiv:2109.12843 [Cs], September 27, 2021. http://arxiv.org/abs/2109.12843.

21.09

• Pang, Yitong, Lingfei Wu, Qi Shen, Yiming Zhang, Zhihua Wei, Fangli Xu, Ethan Chang, and Bo Long. “Heterogeneous Global Graph Neural Networks for Personalized Session-Based Recommendation.” ArXiv:2107.03813 [Cs], July 8, 2021. http://arxiv.org/abs/2107.03813.

• Qiu, Ruihong, Zi Huang, Jingjing Li, and Hongzhi Yin. “Exploiting Cross-Session Information for Session-Based Recommendation with Graph Neural Networks.” ACM Transactions on Information Systems 38, no. 3 (June 26, 2020): 1–23. https://doi.org/10.1145/3382764.

• Qiu, Ruihong, Zi Huang, Tong Chen, and Hongzhi Yin. “Exploiting Positional Information for Session-Based Recommendation.” ArXiv:2107.00846 [Cs], July 9, 2021. https://doi.org/10.1145/3473339.

• Wang, Wen, Wei Zhang, Shukai Liu, Qi Liu, Bo Zhang, Leyu Lin, and Hongyuan Zha. “Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction.” ArXiv:2002.07993 [Cs], April 8, 2021. http://arxiv.org/abs/2002.07993.

  https://github.com/Autumn945/MGNN-SPred

21.08

• Hamilton, William L., Rex Ying, and Jure Leskovec. “Inductive Representation Learning on Large Graphs.” ArXiv:1706.02216 [Cs, Stat], September 10, 2018. http://arxiv.org/abs/1706.02216.

  http://snap.stanford.edu/graphsage/

• Liu, Siyi, Chen Gao, Yihong Chen, Depeng Jin, and Yong Li. “Learnable Embedding Sizes for Recommender Systems.” ArXiv:2101.07577 [Cs], March 11, 2021. http://arxiv.org/abs/2101.07577.

  https://github.com/ssui-liu/learnable-embed-sizes-for-RecSys

• Wu, Felix, Tianyi Zhang, Amauri Holanda de Souza Jr., Christopher Fifty, Tao Yu, and Kilian Q. Weinberger. “Simplifying Graph Convolutional Networks.” ArXiv:1902.07153 [Cs, Stat], June 20, 2019. http://arxiv.org/abs/1902.07153.

  https://github.com/Tiiiger/SGC

• Chen, Jiawei, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, and Xiangnan He. “Bias and Debias in Recommender System: A Survey and Future Directions.” ArXiv:2010.03240 [Cs], October 7, 2020. http://arxiv.org/abs/2010.03240.

21.07

• Yu, Zeping, Jianxun Lian, Ahmad Mahmoody, Gongshen Liu, and Xing Xie. “Adaptive User Modeling with Long and Short-Term Preferences for Personalized Recommendation.” In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 4213–19. Macao, China: International Joint Conferences on Artificial Intelligence Organization, 2019. https://doi.org/10.24963/ijcai.2019/585.

  https://github.com/zepingyu0512/sli_rec

• Chang, Jianxin, Chen Gao, Yu Zheng, Yiqun Hui, Yanan Niu, Yang Song, Depeng Jin, and Yong Li. “Sequential Recommendation with Graph Neural Networks.” ArXiv:2106.14226 [Cs], June 27, 2021. http://arxiv.org/abs/2106.14226.

• Wu, Le, Xiangnan He, Xiang Wang, Kun Zhang, and Meng Wang. “A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation.” ArXiv:2104.13030 [Cs], April 27, 2021. http://arxiv.org/abs/2104.13030.

• Hu, Yang, Haoxuan You, Zhecan Wang, Zhicheng Wang, Erjin Zhou, and Yue Gao. “Graph-MLP: Node Classification without Message Passing in Graph.” ArXiv:2106.04051 [Cs], June 7, 2021. http://arxiv.org/abs/2106.04051.

  https://github.com/yanghu819/Graph-MLP

21.06

• Wang, Shoujin, Liang Hu, Yan Wang, Xiangnan He, Quan Z Sheng, Mehmet Orgun, Longbing Cao, Francesco Ricci, and Philip S Yu. “Graph Learning Based Recommender Systems: A Review,” n.d., 10.

21.05

• Chen, Tianwen, and Raymond Chi-Wing Wong. “Handling Information Loss of Graph Neural Networks for Session-Based Recommendation.” In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 1172–80. Virtual Event CA USA: ACM, 2020. https://doi.org/10.1145/3394486.3403170.

  https://github.com/twchen/lessr

• Ding, Yujuan, Yunshan Ma, Wai Keung Wong, and Tat-Seng Chua. “Leveraging Two Types of Global Graph for Sequential Fashion Recommendation.” ArXiv:2105.07585 [Cs], May 17, 2021. http://arxiv.org/abs/2105.07585.

21.04

• Choi, M., Lee, J., Shim, H., & Lee, J. (2021). Session-aware Linear Item-Item Models for Session-based Recommendation. arXiv preprint arXiv:2103.16104. https://arxiv.org/pdf/2103.16104.pdf

• Wang, Ziyang, Wei Wei, Gao Cong, Xiao-Li Li, Xian-Ling Mao, and Minghui Qiu. “Global Context Enhanced Graph Neural Networks for Session-Based Recommendation.” In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 169–78. Virtual Event China: ACM, 2020. https://doi.org/10.1145/3397271.3401142.

  https://github.com/CCIIPLab/GCE-GNN

• Ying, Rex, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, and Jure Leskovec. “Hierarchical Graph Representation Learning with Differentiable Pooling.” ArXiv:1806.08804 [Cs, Stat], February 20, 2019. http://arxiv.org/abs/1806.08804.

  https://github.com/RexYing/diffpool

21.03

• Quadrana, Massimo, Paolo Cremonesi, and Dietmar Jannach. “Sequence-Aware Recommender Systems.” ArXiv:1802.08452 [Cs], February 23, 2018. http://arxiv.org/abs/1802.08452.

• Yuan, Fajie, Xiangnan He, Haochuan Jiang, Guibing Guo, Jian Xiong, Zhezhao Xu, and Yilin Xiong. “Future Data Helps Training: Modeling Future Contexts for Session-Based Recommendation.” In Proceedings of The Web Conference 2020, 303–13. Taipei Taiwan: ACM, 2020. https://doi.org/10.1145/3366423.3380116.

  https://github.com/fajieyuan/grec

• Ying, Haochao, Fuzhen Zhuang, Fuzheng Zhang, Yanchi Liu, Guandong Xu, Xing Xie, Hui Xiong, and Jian Wu. “Sequential Recommender System Based on Hierarchical Attention Networks.” In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 3926–32. Stockholm, Sweden: International Joint Conferences on Artificial Intelligence Organization, 2018. https://doi.org/10.24963/ijcai.2018/546.

20.11

• Huang, Bo, Ye Bi, Zhenyu Wu, Jianming Wang, and Jing Xiao. “UBER-GNN: A User-Based Embeddings Recommendation Based on Graph Neural Networks.” ArXiv:2008.02546 [Cs], August 6, 2020. http://arxiv.org/abs/2008.02546.

• Chen, Xu, Hongteng Xu, Yongfeng Zhang, Jiaxi Tang, Yixin Cao, Zheng Qin, and Hongyuan Zha. “Sequential Recommendation with User Memory Networks.” In Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining - WSDM ’18, 108–16. Marina Del Rey, CA, USA: ACM Press, 2018. https://doi.org/10.1145/3159652.3159668.

20.10

• Qin, Jiarui, Kan Ren, Yuchen Fang, Weinan Zhang, and Yong Yu. “Sequential Recommendation with Dual Side Neighbor-Based Collaborative Relation Modeling.” Proceedings of the 13th International Conference on Web Search and Data Mining, January 20, 2020, 465–73. https://doi.org/10.1145/3336191.3371842.

  https://github.com/qinjr/SCoRe

20.09

更新文章如下：

• Fang, Hui, Danning Zhang, Yiheng Shu, and Guibing Guo. “Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations.” ArXiv:1905.01997 [Cs], November 26, 2019. http://arxiv.org/abs/1905.01997.

• Wang, Shoujin, Liang Hu, Yan Wang, Longbing Cao, Quan Z. Sheng, and Mehmet Orgun. “Sequential Recommender Systems: Challenges, Progress and Prospects.” In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 6332–38. Macao, China: International Joint Conferences on Artificial Intelligence Organization, 2019. https://doi.org/10.24963/ijcai.2019/883.

• Pan, Zhiqiang, Fei Cai, Yanxiang Ling, and Maarten de Rijke. “Rethinking Item Importance in Session-Based Recommendation.” ArXiv:2005.04456 [Cs], May 9, 2020. http://arxiv.org/abs/2005.04456.

• Liu, Feng, Weiwen Liu, Xutao Li, and Yunming Ye. “Inter-Sequence Enhanced Framework for Personalized Sequential Recommendation.” ArXiv:2004.12118 [Cs], April 28, 2020. http://arxiv.org/abs/2004.12118.