[51] Lei Bai, Lina Yao, Can Li, Xianzhi Wang, and Can Wang. Adaptive graph convolutional recurrent network for traffic forecasting. volume 33, pages 17804-17815, 2020.
[52] Kan Guo, Yongli Hu, Yanfeng Sun, Sean Qian, Junbin Gao, and Baocai Yin. Hierarchical graph convolution network for traffic forecasting. In Proceedings of the AAAI conference on artificial intelligence, volume 35, pages 151-159, 2021.
[53] Yulin Shen, Ziheng Chen, Gong Cheng, and Yuzhong Qu. Ckgg: A chinese knowledge graph for high-school geography education and beyond. In The Semantic Web - ISWC 2021 - 20th International Semantic Web Conference, ISWC 2021, Virtual Event, October 24-28, 2021, Proceedings, pages 429-445, 2021.
[54] Shumin Deng, Hui Chen, Zhoubo Li, Feiyu Xiong, Qiang Chen, Mosha Chen, Xiangwen Liu, Jiaoyan Chen, Jeff Z Pan, Huajun Chen, et al. Construction and applications of open business knowledge graph. arXiv preprint arXiv:2209.15214, 2022.
[55] Brian Walsh, Sameh K Mohamed, and Vít Nováček. Biokg: A knowledge graph for relational learning on biological data. In CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020, pages 3173-3180, 2020.
[56] Ningyu Zhang, Zhen Bi, Xiaozhuan Liang, Siyuan Cheng, Haosen Hong, Shumin Deng, Jiazhang Lian, Qiang Zhang, and Huajun Chen. Ontoprotein: Protein pretraining with gene ontology embedding. arXiv preprint arXiv:2201.11147, 2022.
[57] Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. Knowledge graph embedding by translating on hyperplanes. In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27-31, 2014, Quebec City, Quebec, Canada, pages 1112-1119, 2014.
[58] Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu. Learning entity and relation embeddings for knowledge graph completion. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 25-30, 2015, Austin, Texas, USA, pages 2181-2187, 2015.
[59] Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel. A three-way model for collective learning on multi-relational data. In Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, June 28 - July 2, 2011, pages 809-816, 2011.
[60] Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel. Convolutional 2d knowledge graph embeddings. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, AAAI 2018, New Orleans, Louisiana, USA, February 2-7, 2018, pages 1811-1818, 2018.
[61] Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chengjin Xu, Shirui Pan, Chuan Zhou, and Steffen Staab. Ultrahyperbolic knowledge graph embeddings. In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022, pages 2130-2139, 2022.
[62] Roshni G. Iyer, Yunsheng Bai, Wei Wang, and Yizhou Sun. Dual-geometric space embedding model for two-view knowledge graphs. In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022, pages 676-686, 2022.
[63] Chengbiao Yang and Guilin Qi. An urban traffic knowledge graph-driven spatial-temporal graph convolutional network for traffic flow prediction. In Proceedings of the 11th International Joint Conference on Knowledge Graphs, pages 110-114, 2022.
[64] Jiyuan Tan, Qianqian Qiu, Weiwei Guo, and Tingshuai Li. Research on the construction of a knowledge graph and knowledge reasoning model in the field of urban traffic. Sustainability, 13(6):3191, 2021.
[65] Jia Liu, Tianrui Li, Shenggong Ji, Peng Xie, Shengdong Du, Fei Teng, and Junbo Zhang. Urban flow pattern mining based on multi-source heterogeneous data fusion and knowledge graph embedding. IEEE Transactions on Knowledge and Data Engineering, 2021.
[66] Ling Zhao, Hanhan Deng, Linyao Qiu, Sumin Li, Zhixiang Hou, Hai Sun, and Yun Chen. Urban multisource spatio-temporal data analysis aware knowledge graph embedding. Symmetry, 12(2):199, 2020.
[67] Chenyi Zhuang, Nicholas Jing Yuan, Ruihua Song, Xing Xie, and Qiang Ma. Understanding people lifestyles: Construction of urban movement knowledge graph from gps trajectory. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017, pages 3616-3623, 2017.